Built in Juypter Notebook utilizing Pandas, Numpy, Sklearn, Matplotlib, Seaborn, and Scipy. View the project link for access to our report in the form of a Jupyter Notebook. This project explores how qualities of Massachusetts' school districts impact students' access to higher education. Using data from the state's Department of Elementary and Secondary Education, we will examine district-level data concerning teacher salaries, how students are disciplined, demographics, AP testing, and financial expenditures. Along with visualizing and analyzing the correlations between variables, we tested and tuned multiple machine learning regression models on the data. This led to the conclusions that the best predictive model for this regression machine learning task is the Ridge regression.