For solving the reliability inference problem in the multi-connected knowledge network model, a clique tree propagation algorithm is innovatively applied to the evidential network.Firstly, the multi-connected knowledge network model is clustered as a clique tree, and the joint belief function is regarded as the main parameter of the cluster nodes, therefore, the information each node is obtained, which facilitates the possibility of reliability inference within the multi-connected knowledge network model. In the process of evident fusion of the joint belief function, two new union and intersection methods are introduced to improve the existing DSmT theory, which helps to eliminate the influence of conflicting evident information on other evident variables. Finally, an example is given to illustrate the feasibility of the proposed method.