This project uses three algorithms (logistic regression, decision tree, and random forest) in predicting breast cancer outcomes. The outcomes showed that the Random Forest algorithm had the most accuracy in foreseeing breast cancer disease with a score of 96.491% in the breast malignant growth dataset from Kaggle.