In recent years, with the Chinese government’s emphasis on the development of the cold chain logistics market for fresh agricultural products, the rapid development of agricultural cold chain logistics has been promoted in many aspects. However, in the circulation of fresh agricultural products, there is still a serious problem of “broken chain” leading to a high corrosion rate. Therefore, this research has analyzed the uncertain factors affecting the cold chain distribution system based on fault tree model, and then transform it into Bayesian network to evaluate the reliability of the cold chain distribution system for fresh agricultural product, and identify the key factors affecting the reliability of the cold chain distribution system through calculated probability importance of each node. Then we have constructed nonlinear equations with the limit of the cost, based on reliability allocation method to improve the system reliability. Numerical examples are given to validate the proposed models. The optimization result shows that higher reliability value assigned to the factors with high probability importance is more conducive to the improvement of system reliability.