Searching and watching videos on YouTube has become a part of our daily lives. By understanding the popularity of online videos and predicting the popularity of future videos is of great importance to organizations as well as individuals who are looking forward to publishing their videos. This research aims to predict the popularity of video with help of Classification Algorithms and suggestion of trending and frequently used tags in the form of word cloud. Here, the researcher has used Decision Tree, Support Vector Machines and Naïve Bayes algorithms for training the prediction model. The results provide a good accuracy of popularity prediction which were compared using percentage split test method.