The emerging growth of computer networks and the great influence of Internet on various aspects of trade made using users? information to improve the performance of systems an ordinary task. Currently almost all the user modeling frameworks catch the required information from the application layer, thus just the information providers could use them. As a result, these frameworks have no benefit for the inbetween nodes such as ISPs which may access these data in network layer. In this paper we propose a new multi-agent framework which can be used for modeling the users by network layer information. This framework can help the in-between nodes to arrange their service policies based on different user models. Although using intelligent agents and artificial intelligence techniques, the framework extracts the hidden relations between network layer behavior components and application layer behavior components, thus improving the modeling performance. Moreover we have presented a case study which models an ordinary ISP?s users and shows how the model can be used to improve the ISP?s quality of service.