In this project, I used supervised learning techniques on the data collected for the U.S. census to help CharityML to identify people most likely to donate to their cause. I first explored the data to learn how the census data is recorded, and then applied series of transformations and preprocessing techniques to manipulate the data into a workable format.Then I evaluated several supervised learners considering which is best suited for the solution. Finally, I optimized the model to improve it's perfomance.