This paper proposes a method for estimating the diseases that need the largest medical resources from electronic receipt data. The proposed method uses Diagnosis Procedure Combination (DPC) data in which the diseases that need the largest medical resources are specified as training sets. From the training sets, the proposed method extracts pairs of feature vectors calculated from medical care information and labels of the diseases, which are used to train a classifier. Then the use of the classifier enables estimation of the diseases from electronic receipt data. This paper considers realization of more accurate estimation technique of the deseases that need the largest medical resources by using multiple kinds of classifiers.