This objective of this study is to develop a knowledge acquisition and refinement method for a credit rating problem. A corporate credit rating table (CRT) and a genetic algorithm are integrated to extract and refine the knowledge of multi-criteria for the CRT. The obtained knowledge supports to find optimal parameters of the CRT for our loan decision making. The results show that the knowledge acquisition and refinement method is effective for the CRT as a multi-attribute decision problem.