Advances in Age Estimation Using Facial Sutures: Current Status, Challenges, and Future Perspectives

Forensic age estimation is a fundamental component of biological profiling for unidentified skeletal remains, particularly in mass casualty incidents where specimens are frequently fragmented or incomplete. This review evaluates the diagnostic utility of craniofacial suture closure—specifically across four facial regions—as a non-invasive methodology for age determination in adults. By analyzing the predictable fusion patterns of ectocranial and endocranial sutures, forensic practitioners can derive approximate age ranges when postcranial indicators are absent or unreliable. Despite its utility, the reliability of suture-based estimation remains a subject of academic debate. The rate of closure is influenced by a complex interplay of environmental and biological factors, including nutritional status, hormonal influences, and mechanical loading. Historically, the method has faced criticism due to significant inter-individual variability and limited sample sizes in cadaveric studies. To improve precision and novel detail, this review explores the integration of emerging technologies such as artificial intelligence (AI) and machine learning (ML). These tools can process extensive cranial datasets to identify subtle morphological patterns that may elude human observation. While craniofacial suture analysis remains an essential resource in the forensic toolkit, its accuracy is contingent upon accounting for multi-factorial biological factors. The authors emphasize the necessity for further external validation across diverse global populations to ensure the generalizability and refinement of the technique in forensic medicine and osteology.