Twitter is one of the most common platforms that people share their ideas about any topic. Also, Twitter provides huge database for researchers and analysts and also for companies. However, this infinite data crates some difficulties. The most important difficulty is that there is huge amount of text data, therefore you need to analyze the results and develop methods for the evaluation. This disadvantage contributes to make long time for analyzing data. Sentiment analysis is that natural language processing, text analysis and computational linguistics to identify and extract subjective information in source materials. Sentiment analysis is the most common technique for natural language processing in order to understand human languages. In spite of the fact that sentiment analysis has many sections, we interest on “Sentiment Prediction” by classifying the words as “positive”, “negative” or “neutral”. This is the main aim of our project.