Through this project, we aim to build a linear regression model for automated essay grading. Essays form a huge part of certain college applications and are a part of major competitive exams such as GRE, GMAT etcetera. Manually grading the essays can be extremely time consuming and pressurizing for the instructor. To make these tasks simple, we can train an essay grading program to do the grading automatically. The aim of the grader would be to predict the score of the essay with as much accuracy as possible. The machine assigns scores and should be near the human grader’s score. A dataset of around 2000 essays was used. The essays were graded on the basis of parameters like word count, coherence, number of long words, correct grammar, etc. Feature selection is used to arrive at the most accurate score prediction.