With the rapid growth of the World Wide Web, finding useful information from the Internet has become a critical issue. Automatic classification of user navigation patterns provides a useful tool to solve these problems. In this paper, we propose an approach for classification of users’ navigation patterns and prediction of users’ future requests. Users’ profiles are constructed based on Web log server files and one of clustering methods is implemented to users’ profiles for assigning navigation patterns. Finally, using neural network, recommender engine produces a relevant recommendation list of web pages to the active user. The preliminary results indicate that the proposed approach has high accuracy and coverage in prediction of users’ future requests.