A method for solving multiple attribute decision making (MADM) is proposed based on proximal support vector regression machine (PSVRM). The proposed method extracts learning samples from the MADM problem,estimates the multiple attribute utility function,and then sorts the alternatives. It has less number of parameter and is simple and reliable; the kernel does not need to satisfy the Mercer''s condition. An example demonstrates its feasibility and availability.