Executive Summary: This paper is a demonstration of how machine learning can be used to optimize pursuing leads in sales. In a bank’s phone marketing campaign, whether a sale was closed or not is predicted using a Random Forest based on customer data like history with the company, occupation and age. The final model correctly identifies a closed lead 69% of the time (True Positive Rate), and misidentifies a lead that doesn't close as one that does 17% of the time (False Positive Rate).