Web Recommendation system attempts to predict the user next browsing activity then recommend the web pages items that are likely to be of interest to the user. The ability of predicting the next visited pages and recommending it to the short term navigation user (anonymous user) is highly needed. This research focuses on improving the prediction of the next visited web pages and introduces them to current anonymous user. An enhanced classification algorithm is used to assign the current anonymous user to the best web navigation profile. As the users’ interests change over time, the recommender system has the ability to modify the current web navigation profiles and keep them updated. These adaptive profiles help the prediction engine to predict and then recommend the next visited pages to the current user in an accurate manner.