Hollywood is a multi-billion dollar industry which releases more than a hundred films a year, with large variations in the budgets and box office grosses of the movies. Identifying which factors are important to a movie's profitability and subsequently predicting the success of a movie given its relevant parameters could save movie studios hundreds of millions of dollars a year. This paper analyses the efficiency of using multiple linear regression and Support Vector Machine Classification to predict the box-office success of movies, while analysing the influence of variables like trailer views, Wikipedia page views, critic ratings and time of release. © 2017 IEEE.