It is very important for entertainment lovers to get the review of the movie before they spend for it. There are many different sources from which the reviews can be checked and so it will be a time consuming process to summarize the review from different sources after reading them. In this case, sentiment analysis can help a lot by extracting important information like the negative as well as positive points for the movie and all-round feedback of movie. The response will be subjective but can help the users to decide if the movie is suitable for them or not. In this case there are two methods which are pre-trained for bidirectional relationship with the speech which focus on the words with precision. There are more than 40k reviews which are used for the models. The dataset is combination of data from IMDB and rotten tomatoes. The pre-cleaning of the dataset was done by removing the duplicate entries of movie reviews. In this case the movie’s overall performance will be predicted and expressed so that the movie lovers can take final decision on the basis of results.