Analyzed the effects of different features such as actor rating, director rating and genre on the rating of a movie from a 3GB open dataset taken from IMDb. The insights were that a movie rating is highly dependent on the rating of its directors & actors. Linear regression, Decision Tree, Random Forest and SVM models were developed and compared. Linear Regression performed the best with an accuracy of 83.9%. The only uncertainty in the model is that the movie plot's effect is not taken into account for predicting the movie rating. The image shows the poster of the project.