The Recidivism Forecasting Challenge, organized by the National Institute of Justice, focused on developing models to predict recidivism among individuals on parole. Our team created a solution that balanced predictive accuracy with fairness considerations across different demographic groups. The approach combined traditional machine learning techniques with methods designed to mitigate bias in prediction outcomes.