The performance evaluation of Web applications usually requires the utilization of sequences of user requests for determined Web pages. These sequences can be obtained, for example, by applying empirical methods (recording the real sequence of requests), or by applying a formal model for generating synthetic results. In this paper, we present our Web Browsing Model and the User Centric Walk algorithm as its implementation. By taking into account the hyperlink structure as well as the different user behavior on the Web, this algorithm allows us to generate accurate synthetic data that can be used instead of empirically obtained requests. As another contribution of this paper we have shown, based on empirical data, that the probability of choosing some hyperlink from a given page as well as the probability a user leaves a page without following a hyperlink is best characterized by a power-law. Moreover, we show the flexibility and applicability of our model by performing the required correlations to empirical data, which validate our approach.