Mobile ad hoc networks (MANETs) are a very promising next generation networks. Prediction is an essential aspect in the deployment of MANETs. Current work mainly focuses on mobility prediction: prediction of spatio-temporal trajectories of nodes. Web page prefetching based on prediction of user’s behavior has been shown to decrease latency in wired networks. Current models of prefetching focus on what to prefetch and not when. Since routing information changes with time in MANETs, the expected time of user’s access is also important. In this paper we integrate prefetching algorithms with mobility models and personalized to user browsing patterns. This not only reduces latency but also ensures just-in-time prefetching.