Aims: High naevus counts, and UV photodamage are strong melanoma risk factors. However, whole-of-body measures fail to capture variability across body sites. Three-dimensional (3D) total body photography (TBP) and artificial intelligence (AI) allows the opportunity to automate the extraction of site-specific distributions of naevi and photodamage. This study combined 3D-TBP, AI, and unsupervised clustering in a high-risk cohort to identify distinct phenotypic patterns associated with melanoma.