Every year the number of movie produced and released surpass the previous year's count and so do the total box office collections. So in this quality centric industry, it becomes imperative that the movie succeeds both in terms of box office collections and critical reviews and also renders profit. Due to advent of predictive analytics and big data generated through various social interactions, models to predict accurately the total gross of a movie can be devised, which eventually help the movie studio by giving constructive feedback both in pre-production and post-production phase. So the availability of this data gathered from various social platforms like IMDb, YouTube and Wikipedia can help to gauge the society's reaction and response towards a particular movie. It can also foretell a society's anticipation towards a particular movie. In this paper, we have built predictive models by establishing links between classical features, social media features and the overall success of the movie which includes total box office collection and the critics rating or review. The results show that the prediction model built using integration of classical as well as social factors can achieve higher accuracy rate. © 2016 IEEE.