This study developed a schizophrenia classification model using Radiomic Tractometry and compared the performance of RF, XGB, and LGBM models. The XGB model showed the best performance with an AUC of 0.80, while the RF and LGBM models recorded AUCs of 0.78, respectively. This study successfully captured localized white matter abnormalities by leveraging texture- and first order-based features, suggesting that Radiomic Tractometry, through the simultaneous analysis of multiple tracts, can serve as a powerful tool for identifying structural biomarkers of schizophrenia.