In order to improve the comprehensive quality of the laser cladding layer of the remanufactured workpiece, the laser power, the powder feeding amount and the scanning speed are selected as the optimization variables, and the aspect ratio, dilution rate and powder collection rate of the cladding layer are selected as optimization targets, based on the comprehensive weighting method. The analytic hierarchy process is used to transform the three optimization objectives into comprehensive quality objectives, design the whole factor experiment, and use the MATLAB software to establish the BP neural network prediction model based on the experimental results, and determine the combination of the best process parameters by genetic algorithm. The optimal process parameters for re-manufacturing laser cladding of equipment parts are: laser power is 3.0 kW, powder feeding is 47 g/min, and scanning speed is 5.5 mm/s.