Corticobasal syndrome (CBS) and progressive supranuclear palsy (PSP) are classic clinical syndromes derived from 4R tau pathology. Differential clinical diagnosis remains difficult due to neurodegenerative overlap. Most previous studies have assessed white-matter (WM) degeneration using cross-sectional data. This study applied Subtype & Stage Inference (SuStaIn), a novel unsupervised machine-learning technique for regional WM fractional anisotropy based on cross-sectional brain diffusion MRI to identify differences in temporal progression patterns of WM degeneration between CBS and PSP. Results suggested the utility of SuStaIn for identifying temporal WM degeneration patterns in and classifying patients with CBS and PSP.