This project aimed to predict the sale price for a piece of heavy machinery based upon historical sale prices at auction for a variety of types of heavy machinery. The data was obtained from the Blue Book for Bulldozers Kaggle competition. The dataset consisted of a total of 412,698 observations with 53 features (including the target variable).   The best model was found to be a Random Forest, having an RMSLE of 0.266221. The GitHub repository can be found here.