To deal with the design of remanufacturing reverse logistics network, considering the uncertainty of the product recovery and consumer market demand, a multi-period remanufacturing reverse logistics network model based on third-party recovery was established in order to maximize the benefits of both the third-party logistics supplier and the manufacturer. The model can be determined for the best price of products that the manufacturer pays for the third-party logistics supplier each period. The numbers of recycling centers and inspection/disassembly centers, and the allocation of the corresponding goods flows in the network can be decided. The uncertainty parameters were denoted by the triangular fuzzy numbers. With fuzzy chance constrained programming methods, the network model in the uncertain environment can be transferred into a certainty equivalent model. The validity of the model was illustrated by a numerical example, and the relationship between the two goals was analyzed by goal programming method.