Amadeus Airport On-Time Performance
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For Agents
Predict on-time departure probability for a given airport and date. Agents call /airport/predictions/on-time to flag risky itineraries before booking.
Use for: I want to check whether flights from JFK are likely to leave on time tomorrow, Find the on-time performance prediction for Heathrow on a specific date, Get the probability that flights depart on time from CDG next Monday, Check whether a connection through Frankfurt is risky on my travel date
Not supported: Does not return per-flight delays, live flight status, or arrival predictions — use for predicted on-time departures from a single airport on a single date only.
The Amadeus Airport On-Time Performance API predicts the probability that flights from a given airport will depart on time on a specified date. The single GET endpoint at /airport/predictions/on-time accepts an airport IATA code and a date and returns a probability score derived from historical performance and forecast conditions. It is used to flag risky connections and to decide whether to recommend buffer time on multi-leg itineraries.
Install Jentic One Beta
Connect the Airport On-Time Performance to your agent
Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Airport On-Time Performance, 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.
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Step 1: Jentic One Host machine
# On the machine that will host your Jentic One instance:
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh2
Step 2: Agent machine
# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | 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 Airport On-Time Performance API.
Predict the on-time departure probability for an airport on a future date
Compare predicted reliability across alternative connecting airports
Flag itineraries with high disruption risk before booking confirmation
Recommend longer connection buffers when predicted on-time score is low
Pull predictions for a planned travel date to inform itinerary advice
Use Cases
Patterns agents use Airport On-Time Performance API for, with concrete tasks.
★ Connection Risk Assessment
When a traveller is choosing between two itineraries, surface the predicted on-time performance of the connecting airport on the travel date. The /airport/predictions/on-time endpoint returns a probability score that can be displayed alongside layover duration, so the user knows whether a 60-minute connection at a low-reliability airport is sensible. This is more accurate than static airport rankings because the prediction reflects the specific date.
Call /airport/predictions/on-time for ORD on 2026-09-15 and report the on-time probability score.
Travel Insurance Pricing
Travel insurers and trip-protection products can price disruption coverage using the predicted on-time score for the departure and connecting airports. A higher predicted reliability lowers the expected payout for missed-connection cover, which feeds directly into a dynamic premium. The single-endpoint design keeps the call cheap enough to run inline at quote time.
Fetch on-time predictions for FRA and IAD on 2026-10-04 and feed both scores into the premium calculation.
Operations Buffer Planning
Corporate travel managers planning multi-leg itineraries can use predicted on-time scores to decide whether to recommend a longer ground-transfer buffer. A predicted reliability below a threshold triggers the booking tool to require at least 2 hours between flights, reducing disruption tickets opened with the support team.
Look up the on-time score for the user's connecting airport and require a 2-hour buffer if the score falls below 0.7.
Agent Itinerary Advisor
An AI travel agent comparing two itineraries can call the prediction endpoint for each connecting airport to recommend the more reliable route. Through Jentic the agent searches for 'predict airport on-time performance', loads the schema, and runs the lookup against each candidate hub. The agent then summarises the trade-off between price and reliability for the user.
Use Jentic to call the on-time prediction endpoint for each of two candidate connecting airports and recommend the higher-scoring option.
Key Endpoints
1 endpoints — the amadeus airport on-time performance api predicts the probability that flights from a given airport will depart on time on a specified date.
METHOD
PATH
DESCRIPTION
GET
/airport/predictions/on-time
Predict on-time departure probability for an airport
GET
/airport/predictions/on-time
Predict on-time departure probability for an airport
Why Jentic?
Three things that make agents converge on Jentic-routed access.
Credential isolation
Amadeus client credentials are stored encrypted in the Jentic vault (MAXsystem). Jentic exchanges them for a short-lived bearer token at execution time so the raw secret never enters agent context.
Intent-based discovery
Agents search Jentic for 'predict airport on-time performance' and Jentic returns the /airport/predictions/on-time operation with its input schema, removing the need to scan the Amadeus self-service docs first.
Time to first call
Direct Amadeus integration: half a day to wire OAuth, the request, and a caching layer. Through Jentic: under fifteen minutes — search, load, execute.
Related APIs
Alternatives and complements available in the Jentic catalogue.
FAQs
Specific to using Airport On-Time Performance API through Jentic.
What authentication does the Airport On-Time Performance API use?
The API uses the Amadeus OAuth 2.0 client-credentials flow. Exchange API key and secret at the Amadeus token endpoint and send the bearer token on the /airport/predictions/on-time request. Jentic keeps the credentials in the encrypted vault and refreshes the token automatically.
What does the on-time probability score represent?
The score is the predicted likelihood that flights departing the supplied airport on the supplied date will leave on time. It is a forward-looking estimate derived from historical performance, not a record of past flights, so it is most useful for itineraries that have not yet been flown.
What are the rate limits for the Airport On-Time Performance API?
Rate limits are not declared in the OpenAPI spec and depend on the Amadeus contract tier. The endpoint is read-only and cacheable for the same airport and date, so cache aggressively to stay under the per-second cap for your account.
How do I check on-time risk for a flight through Jentic?
Run pip install jentic, then use the search query 'predict airport on-time performance'. Jentic returns the /airport/predictions/on-time operation, you load the schema, supply airportCode and date, and execute. The score can then drive a recommendation in your itinerary UI.
Can I get a per-flight prediction or only per-airport?
This endpoint is per-airport per-date — it predicts overall on-time performance for departures from the supplied airport. For per-flight delay predictions Amadeus offers a separate Flight Delay Prediction API that takes a specific carrier, route, and departure time.
Is the Airport On-Time Performance API free?
Amadeus self-service APIs include a free test environment with quota limits and a paid production tier. Production pricing depends on transaction volume and is set by contract — confirm current rates in the Amadeus self-service developer portal.
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