• Identified age at release, gang affiliation, and employment status as significant predictors of recidivism with 76.5% accuracy using R-based Stepwise Selection and Chi-Square analysis in logistic regression. • Implemented Decision Tree analysis using R, identifying critical employment thresholds that differentiate recidivism probabilities, with employment status influencing recidivism predictions at a key threshold of 64.3% days employed.