Using multifactor dimensionality reduction approach, the four-factor model, including smoking status, OGG1 S326C (rs1052133), APEX1 D148E (rs3136820), and ADPRT762 (rs1136410), had the best ability to predict bladder cancer risk with the highest cross-validation consistency (100%) and the lowest prediction error (37.02%; P < 0.001).