Using data centered around the measurement of a variety of tumors, we created 3 machine learning models and compared the performance of each in classifying tumors as malignant or benign. We catered our approach, explanation, and demo towards medical professionals and explained a variety of model performance metrics, as misdiagnosing a tumor could have dramatic consequences. Due to this, we prioritized sensitivity over accuracy as we do not wish for a malignant tumor to go undetected while also considering specificity in order to avoid in unnecessary invasive surgery.