The Chicago Car Accident Injury Prediction Algorithm was about predicting Severe injuries from car crashes. The idea would be to inspire the city to hire more EMTs and ambulances to prevent Severe injuries.  The data went through a rigorous data cleansing process.  Logistic Regression was used for all three models. Because the idea was to have a best model. The models ran through single and double cross-validation to pick the best model. Besides the cross-validation,  three different confusion matrixes were made.  The statistics of the confusion matrix were evaluated and discussed.