Although white matter tract microstructure has been implicated in treatment outcome of schizophrenia, its predictive capability on first-episode patients remains unknown. In the study, diffusion spectrum imaging (DSI) data were acquired from both chronic and first-episode patients, reconstructed by mean apparent propagator (MAP) MRI and analyzed with tract-based automatic analysis (TBAA). Stepwise statistical analysis was then performed to identify specific segments of white matter tracts that were significantly different between remitted and non-remitted chronic patients. We built a support vector classifier on the preprocessed data matrix. The resulting model yielded fair validation and test accuracy on chronic and first-episode patients, respectively.