In recent years, the market of electric vehicles (EVs) has developed rapidly across the world, and recycling a large number of their spent power batteries has become an urgent challenge today. The resulting closed-loop supply chain (CLSC) have been considerably studied under different aspects. However, there is a lack of research investigating electric vehicle batteries (EVBs) network design under uncertainty. This paper focuses on the issues of quantitative modelling for the network design of a CLSC of used EVBs consisting of power battery manufacturers, EV retailers, collection centers, recycling centers, echelon utilization centers and disposal centers, where power battery manufacturers can remanufacture used EVB products. We investigate a two-stage stochastic mixed-integer programming (SMIP) model to design the network and the model is solved using the Benders Decomposition (BD) method to derive optimal solutions. Numerical experiments show that the SMIP model can effectively hedge against high uncertainty.