In recent years, data platforms such as xROAD have been increasing. Combining these data enables various cross-regional analyses, but analysis using all the data requires ample computing resources, and duplication of data leads to waste in the allocation of analysis resources. In order to solve these problems, this study examined a method to construct a bridge deterioration estimation model by extracting the minimum necessary for the analysis from a large number of explanatory variables. As a result, we confirmed that the accuracy of the model using the explanatory variables narrowed down by our method as teacher data retains some accuracy when all variables are used.