Laser cladding technology with environmental protection and high cost performance has been widely used in the field of workpiece remanufacturing. However, it is difficult to control the quality of cladding layer in remanufacturing process due to the complex nonlinear relationship between laser cladding process parameters and cladding layer quality. To solve the above problem, a multi-objective optimization strategy of laser cladding process parameters for remanufacturing is proposed in this paper, taking microhardness, heat affected zone depth, and porosity as the optimization objectives. This method provides the nonlinear mapping relationship between laser cladding process parameters and optimization objectives based on the support vector mechanism for regression. The process parameters of laser cladding are optimized though multi-objective particle swarm optimization algorithm. On the basis of Pareto solution set, the decision analysis module is constructed by TOPSIS that gets a weight input by analytic hierarchy process, and the optimal parameter selection scheme is found out from Pareto solution set. Finally, the remanufacturing case of steam turbine valve seat parts proves that this method can improve the overall quality of remanufactured products.