Amadeus Flight Delay Prediction
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AI ReadinessNon-Ready (F)0/100
Official vendor OpenAPI document · agent-readyAI/MLMl Inferenceoauth21 EndpointsREST
For Agents
Estimate the probability a scheduled flight will be delayed by 30, 60, or 120+ minutes so an agent can warn travellers, adjust connection planning, or trigger proactive rebooking.
Use for: Predict the probability my flight will be delayed, I want to know how likely flight LH441 is to be late tomorrow, Score this upcoming flight's on-time performance, Check whether the first leg of my connection is at risk of delay
Not supported: Does not return live flight status, actual delay minutes, or rebooking options - use only to estimate delay-segment probabilities for a scheduled flight.
The Amadeus Flight Delay Prediction API estimates the probability that a given scheduled flight will be delayed and assigns it to one of four delay segments - under 30 minutes, 30 to 60, 60 to 120, or over 120 minutes. The single GET endpoint takes the carrier code, flight number, scheduled departure date and time, origin, destination, duration, and aircraft code, and returns probability scores per segment. Travel apps use it to set traveller expectations, suggest tighter or looser connection times, and prioritise rebooking outreach.
Install Jentic One Beta
Connect the Flight Delay Prediction to your agent
Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Flight Delay Prediction, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.
Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.
1
Step 1: Jentic One Host machine
# On the machine that will host your Jentic One instance:
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Famadeus.com%2Famadeus-flight-delay-prediction" | sh2
Step 2: Agent machine
# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Famadeus.com%2Famadeus-flight-delay-prediction" | sh
jentic register # connects your agent to your Jentic One instanceJentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.
Capabilities
What an agent can do with Flight Delay Prediction API.
Estimate probability of delay across four segments (under 30 min, 30-60, 60-120, 120+) for a given scheduled flight
Score upcoming flights in a traveller's itinerary by likely on-time performance
Flag connecting itineraries with high delay probability on the first leg
Trigger proactive traveller communications when a high-delay-probability flight is approaching
Compare expected reliability across alternative carriers on the same route
Use Cases
Patterns agents use Flight Delay Prediction API for, with concrete tasks.
★ Proactive Delay Notifications
Travel apps run a daily job over upcoming bookings, call /travel/predictions/flight-delay for each segment, and email or push-notify travellers whose flight has a high probability of falling into the 60-120 or 120+ delay band. This gives passengers time to leave for the airport later or arrange alternative ground transport without the integrator needing real-time operational data feeds.
For each booking departing in the next 24 hours, call /travel/predictions/flight-delay and send a notification when the combined probability for the 60-120 or 120+ band exceeds 25 percent.
Tighter Connection Risk Scoring
Self-service booking flows score the first leg of any connecting itinerary with the delay endpoint and surface a warning when the layover is short relative to the predicted delay range. The scoring takes a few hundred milliseconds per leg and can be cached for an itinerary's lifetime, so the impact on checkout latency is minimal.
Given a two-leg itinerary with a 50-minute layover, score the first leg's delay probability and return a warning if the 30-60 or 60-120 band combined exceeds 30 percent.
Carrier Comparison on a Route
Corporate travel managers compare expected reliability of competing carriers on the same city pair by calling the prediction endpoint for representative future flights from each carrier. Aggregated over a week of departures, the resulting probabilities feed a simple reliability score used in supplier negotiations.
Call the delay-prediction endpoint for one representative flight per carrier on JFK-LHR for the next 7 days and rank carriers by expected probability of an under-30-minute delay.
Agent-Driven Itinerary Risk Check via Jentic
An AI travel concierge calls Flight Delay Prediction through Jentic for each leg of a customer's upcoming trip and includes the delay risk in the daily briefing. Jentic resolves OAuth and parameter shaping, so the agent only describes the intent and supplies flight metadata.
Call jentic.search('predict Amadeus flight delay'), load the operation, and execute it with carrierCode, flightNumber, scheduledDepartureDate, scheduledDepartureTime, departureAirportCode, arrivalAirportCode, aircraftCode, and duration to return per-segment probabilities.
Key Endpoints
1 endpoints — the amadeus flight delay prediction api estimates the probability that a given scheduled flight will be delayed and assigns it to one of four delay segments - under 30 minutes, 30 to 60, 60 to 120, or over 120 minutes.
METHOD
PATH
DESCRIPTION
GET
/travel/predictions/flight-delay
Predict delay segment probabilities for a scheduled flight
GET
/travel/predictions/flight-delay
Predict delay segment probabilities for a scheduled flight
Jentic AI Readiness Score
This API is usable in Jentic One now. Its AI-readiness score against Jentic's framework shows where it stands today and where improvements would make it even easier for agents to use.
F
Flight Delay Prediction
- Non-Ready (F)0/100
100
Foundational Compliance76
Developer Experience & Jentic Compatibility49
AI-Readiness & Agent Experience94
Agent Usability100
Security0
AI DiscoverabilityPowered by JenticScoring Framework 1.0.0 | Scoring Engine 0.4.0
Show dimension breakdown
100
Foundational Compliance
Base layer of spec validity and structural soundness.
Grade: A+Signals: 4
99%
Lint Results
Aggregated quality score from linter diagnostics, weighted by severity.
100%
Resolution Completeness
Percentage of `$ref` references that resolve successfully.
100%
Specification Validity
Checks whether the API description parses successfully and conforms to its declared specification (e.g., OpenAPI).
100%
Structural Integrity
Structural correctness score based on schema issues using logarithmic dampening.
76
Developer Experience & Jentic Compatibility
Clarity, completeness, and ingestion readiness for developers and tooling.
Grade: A-Signals: 4
41%
Example Density
How richly the API is illustrated with examples.
87%
Example Validity
Percentage of examples that conform to their schemas.
75%
Response Coverage
Percentage of operations with complete response definitions (success, client error, server error).
100%
Tooling Readiness
Health of API ingestion, bundling, and resolution within Jentic pipelines.
49
AI-Readiness & Agent Experience
Semantic breadth, depth, and agent comprehension for AI systems.
Grade: D+Signals: 4
46%
Description Coverage
Coverage of descriptions across API elements.
0%
Error Standardization
Coverage of RFC 9457 Problem Details for error responses.
100%
OperationId Quality
Coverage, uniqueness, and casing consistency of operationIds for AI inference.
50%
Summary Coverage
Coverage of summaries across operations/tags/info.
94
Agent Usability
Functional utility, complexity comfort, and AI orchestration readiness.
Grade: A+Signals: 1
94%
Complexity Comfort
Agent comfort level based on API operational and structural complexity.
100
Security
Trust, risk posture, and security compliance.
Grade: A+Signals: 1
100%
Authentication Strength
Average quality of security schemes based on authentication method strength (weakest link for OAuth2).
0
AI Discoverability
Findability, semantic richness, and reasoning readiness.
Grade: FSignals: 1
0%
Descriptive Richness
Clarity and depth of descriptions across API elements.
Score it yourself
Every API in the directory is allowlisted, so you can re-score it with no key required.
npx @jentic/api-scorecard-cli score <openapi-url>Why Jentic?
What agents get from Jentic-routed access to this vendor.
Setup
Wiring the Flight Delay Prediction API by hand means handling the Amadeus OAuth 2.0 client_credentials exchange, refreshing the bearer token, and assembling the query parameters for GET /travel/predictions/flight-delay against the correct Amadeus host and version. Through Jentic you install once, import Flight Delay Prediction from the API Directory, store the Amadeus client credentials once, and your agent calls it.
Permission scoping
The route, date, and carrier details travel as query parameters, not as a resource id in the URL path, so scoping is by operation. You limit the agent to the operations it needs, such as reading the delay-segment probabilities for a scheduled flight, and it cannot reach other Amadeus operations unless you add them.
Credential isolation
Your Amadeus client_id and client_secret are stored once, encrypted, by your own Jentic One instance, which runs the client_credentials exchange and injects a fresh bearer token at execution time. The raw secret never enters the agent's prompt, logs, or context.
Intent-based discovery
Agents search Jentic by intent such as 'predict how likely this scheduled flight is to be delayed', and Jentic returns the /travel/predictions/flight-delay operation with its input schema so the agent supplies the required query parameters without reading the Amadeus docs first.
Related APIs
Alternatives and complements available in the Jentic catalogue.
FAQs
Specific to using Flight Delay Prediction API through Jentic.
What authentication does the Flight Delay Prediction API use?
Amadeus Self-Service OAuth 2.0 client_credentials. Exchange client_id and client_secret at https://api.amadeus.com/v1/security/oauth2/token for a bearer token and pass it in the Authorization header. Through Jentic, the credentials are kept in the encrypted vault and the bearer token is rotated automatically before each prediction call.
Which fields do I have to send to get a prediction?
All eight query parameters are required: originLocationCode, destinationLocationCode, departureDate, departureTime, arrivalDate, arrivalTime, aircraftCode, carrierCode, flightNumber, and duration. Missing any of them returns a 400 from /travel/predictions/flight-delay.
What are the rate limits for the Flight Delay Prediction API?
Amadeus Self-Service Test environment caps prediction endpoints at 10 transactions per second per API key with a fixed monthly quota; Production limits scale with your Self-Service plan tier. Bearer tokens expire after roughly 30 minutes and must be refreshed.
How do I score a flight's delay risk through Jentic?
Run pip install jentic, then call jentic.search('predict Amadeus flight delay'), load the operation, and execute it with the eight required parameters. Jentic handles the OAuth exchange and calls /travel/predictions/flight-delay, returning the delay-segment probabilities.
Does the API tell me the actual delay in minutes?
No. It returns a probability per segment (under 30 min, 30-60, 60-120, 120+). To translate into an expected value, multiply each midpoint by its probability and sum, but treat the output as a risk band rather than a precise prediction.
Is the Flight Delay Prediction API free?
The Test environment is free with limited monthly quota. Production access is metered per transaction under an Amadeus Self-Service plan; pricing is published on the Amadeus for Developers portal.
Can I limit what my agent is allowed to do with the Flight Delay Prediction API?
Yes. Because you self-host Jentic One, your own rules decide which operations and credentials the agent can use, and scoping here works at the operation level since the route, date, and carrier details travel as query parameters rather than a resource id in the URL path. You can allow the agent only the read operation that returns delay-segment probabilities for a scheduled flight from GET /travel/predictions/flight-delay, and it cannot reach any other Amadeus operation unless you add it. The Amadeus client_id and client_secret stay stored and encrypted in your own instance, which runs the OAuth exchange and injects a fresh bearer token at call time, so the raw secret never enters the agent's prompt or logs.
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