Depression is one of the most popular mental illnesses between people. Nowadays, the proportion of the people with this disease increased according to psychologists, it exposes many people to danger and it leads them to suicide. Moreover, sleep, eating, mood, communication, the way of thinking about them self all of it have an effect on a depressed person. We reach the depth of the human through words that affect depressed people to alleviate or treat them. We aim to predict the depression of Twitter users through their Tweets by offering the report of statistics of the user's depression and help reduce it in our application. We provide to all users with a report of statistics of the depression, viewing some yoga exercises, proper tips. For depressed users, we make a direct counseling with a doctor, and show daily depressed tweets. We will gather dataset from tweets by TWINT tool then analyze dataset by preprocessing it from dictionary, so it gives sentiment analysis then classifier by naive bays algorithm. Therefore, it will detect whether a user has depression or not. Finally, we hope to help most of the depressed people perfectly and discover that they have depression from the beginning step before reaching the highest level of diagnosis.