In this paper we propose an advanced Dempster-Shafer (D-S) Evidence Theory based Fuzzy Trust model (ETFT) for Peer-to-Peer (P2P) networks. The primary goal of ETFT is to be able to address trust information uncertainty and fuzzy trust inference to deal with inconsistent or conflicting recommendation problems in a reputation based P2P environment. The D-S theory is therefore introduced to our trust model. To make the D-S theory fit into P2P systems, we creatively revise the combination rules and achieve greatly improved results. To further improve the accuracy and performance, ETFT filters out noisy referrals before combining the evidences. From the theoretical analyses and experimental results, it is evident that the proposed ETFT has a clear advantage in modeling dynamic trust relationship and aggregating recommendation information. Results also demonstrate that ETFT is more robust and can generate higher successful transaction rate than most existing frameworks.