Aiming at the shortage of on-site data samples in equipment maintenance evaluation, a multi-source data fusion method based on D-S evidence theory is established to make full use of the maintenance test data of the early stages or from other sources.Firstly, the traditional Bayes Bootstrap method is improved.The discretized maintenance test data from each source is more accurately fitted to its distribution parameters, then the information such as sample size and distribution characteristics is mined from the data source to construct an evidence.The evidence synthesized by D-S evidence theory is taken as a weight for constructing a multi-source data fusion model of maintenance.Finally, the maintenance test data of a certain type of tank is used to analyze the example, and the effectiveness of the fusion method is verified.