The International Classification of Diseases 10th version (ICD-10) is one of the most standard and important disease classifications. Since computerized ICD-10 coding systems have drawn a great deal of attention in the medical field, a great number of different coding systems have been proposed. The present paper proposes a hybrid architecture of different coding systems. First, given an input disease name, three coding systems output codes with their confidence scores. A C4.5based system selector then selects the best output by using both input statistics and the confidence score from each system. The experimental results demonstrated that the selector significantly boosts the overall performance (+3.4 points).