Abstract: In this paper we consider the problem of webpage usage prediction in a web site by modeling usersĒ navigation history and webpage content with weighted suffix trees. This userĒs navigation prediction can be exploited either in an on-linerecommendation system in a web site or in a webpage cache system. The method proposed has the advantage that it demands a constant amount of computational effort per one userĒs action and consumes a relatively small amount of extra memory space. These features make the method ideal for an on-line working environment. Finally, we have performed an evaluation of the proposed scheme with experiments on various web site log files and webpages and we have found that its quality performance is fairly well and in many cases an outperforming one.