Abstract: Whether to carry out differential maintenance activities and strategy of managing replacement for individual high-voltage cables is based on the analysis of cable reliability. However, the application of conventional Weibull methods to analysis of failure data does not provide information on differential aging status of individual cable condition. In addition, it is difficult to obtain accurate results for traditional statistical models, owing to the limited aging and failure data of high-voltage cables. In this paper, a method is proposed by combining Bayes inference with Weibull proportional hazard model. The relationship between cable reliability and different conditions is established through the Weibull proportional hazard model, and the parameters of the model can be estimated through Bayes inference by combining high-voltage cable related prior information with operational and failure data. Moreover, the reliability of individual cables can be analyzed using the model and the estimated parameters. The proposed method is then applied to the cable data, and it is found that whether to directly bury cables as well as the magnitude of the load rate has a greater impact on the reliability of the high-voltage cable in the studied area. Based on the reliability analysis, the recommendations for differential maintenance and replacement decisions are given. The results of applying the proposed model to 12 faulty and in-service high-voltage cables show that the proposed method can be used to analyze the reliability of high-voltage cables and can make full use of limited data and prior information to give relatively more accurate results, thus proving the feasibility to solve the problem that it is difficult for the existing methods to apply to reliability analysis of individual cable with limited failure data.