  The film industry is one of the most popular entertainment industries and one
of the biggest markets for business. Among the contributing factors to this
would be the success of a movie in terms of its popularity as well as its box
office performance. Hence, we create a comprehensive comparison between the
various machine learning models to predict the rate of success of a movie. The
effectiveness of these models along with their statistical significance is
studied to conclude which of these models is the best predictor. Some insights
regarding factors that affect the success of the movies are also found. The
models studied include some Regression models, Machine Learning models, a Time
Series model and a Neural Network with the Neural Network being the best
performing model with an accuracy of about 86%. Additionally, as part of the
testing data for the movies released in 2020 are analysed.
