Almost all chemical and petrochemical plants in Japan have been operated for 30 years or more. Leakage accidents in piping often occur in such a kind of plants because of CUI (Corrosion Under Insulation) progress. In the worst case, inner fluid leakage might affect human bodies or the environment. Proper predictive maintenance work based of corrosion rate estimation should be performed to prevent the accidents. In the previous research, corrosion rates have been estimated based on databases constructed by cases of past corrosion. However, the method of previous research has some problems, such as the estimation accuracy is insufficient. In this research, a selection support system which can estimate corrosion rates with high accuracy using information gain ratio and reliability is developed.