Exoplanet Prediction

Enter stellar and planetary parameters to predict whether a Kepler Object of Interest (KOI) is a confirmed exoplanet using our Random Forest AI model.

Stellar & Planetary Parameters

Fill in the parameters below. Our AI model will analyze the data and provide a prediction with confidence score.

Orbital Parameters

Orbital Period (days) Time for one complete orbit around the host star

Impact Parameter Minimum distance between planet and star center during transit

Transit Duration (hours) Duration of the transit event

Transit Parameters

Transit Depth (ppm) Depth of the transit signal in parts per million

Signal-to-Noise Ratio Signal-to-noise ratio of the transit model

Planetary Parameters

Planet Radius (Earth radii) Radius of the planet relative to Earth

Equilibrium Temperature (K) Estimated equilibrium temperature of the planet

Insolation (Earth flux) Stellar flux received by the planet relative to Earth

Stellar Parameters

Stellar Effective Temperature (K) Surface temperature of the host star

Stellar Surface Gravity (log g) Logarithm of stellar surface gravity

Stellar Radius (Solar radii) Radius of the host star relative to the Sun

Kepler Magnitude Apparent magnitude in Kepler bandpass

93% Accuracy

Our Random Forest model achieves exceptional accuracy on the Kepler Objects of Interest dataset.

Instant Results

Get predictions in milliseconds using our optimized ensemble learning algorithm.

Scientific Validation

Model trained and validated on confirmed exoplanets from NASA's Kepler mission.