According to the nonlinear characteristics of battle damage assessment (BDA), this study proposes an equipment BDA method based on the belief rule base (BRB) and evidential reasoning (ER) in view of the multi-source and uncertain battle damage data in a complicated battlefield. Firstly, through the analysis of factors affecting BDA, a new BRB-ER model integrating multiple characteristics is presented. Secondly, to solve the problem of inaccurate parameters in the initial BRB of the traditional expert system, we use the local particle swarm optimization algorithm to optimize the initial parameters of the model and thus improve the accuracy of BDA. Finally, a battle damage test is taken as an example to verify and compare methods for equipment BDA based on the reasoning of BRB. The results show that the proposed method can effectively evaluate the equipment BDA and provide assistant support for a commander to make battlefield maintenance decisions.