The quest for precision medicine in autism spectrum disorder (ASD) necessitates quantitative imaging markers that account for individual variability. Traditional case-control studies offer only group-level insights, lacking subject-specific ASD information. A promising alternative is normative modeling, which defines normative developmental trajectory using large neurotypical (NT) data, and neurodevelopmental conditions are measured as individual deviations from this norm. This approach allows for the identification of personalized imaging patterns, which can be precursors to biomarkers. In this study, we applied normative modeling on large-scale diffusion MRI (dMRI) data pooled from 10 sites, aiming to 1) derive imaging markers to characterize each ASD subject, and 2) explore their relationship with autistic traits.