Abstract Forensic odontology has traditionally relied on dental morphology and odontometric measurements for identification and profiling purposes. Innovations in imaging technologies (high-resolution two-dimensional 2D radiography, cone-beam computed tomography CBCT, and intraoral three-dimensional 3D scanning), geometric morphometrics analysis (GMA), and artificial intelligence (AI) have revolutionized the collection, analysis, and interpretation of dental data. Relevant literature was identified through searches in PubMed, Scopus, and Web of Science using the keywords forensic odontology, CBCT, GMA, AI segmentation, and human identification, focusing on English-language studies published between 2010 and 2025. This narrative review consolidates the existing evidence regarding (1) the enhancement of data acquisition and comparability through 2D and 3D imaging; (2) the quantification of dental sexual dimorphism by GMA and its application in machine learning (ML) classifiers; (3) recent advancements in sex-prediction models derived from tooth metrics and 3D shape data; and (4) the facilitation of dental model creation and identification workflows through AI-driven segmentation. The discussion encompasses practical benefits, existing limitations, validation requirements, and prospective directions for the adoption of this technique in forensic applications.
Riaz et al. (Wed,) studied this question.