<![CDATA[Forensic odontology plays a critical role in human identification, yet conventional methods remain time-consuming, subjective, and limited in handling large-scale data, particularly in disaster and military contexts. This study aims to systematically review the utilization of artificial intelligence in forensic odontology and to develop a contextual role model for implementation at RSAL dr Mintohardjo. A systematic review design was employed by analyzing peer-reviewed articles from major databases published between 2014 and 2025 using predefined inclusion criteria and thematic synthesis. Findings indicate that artificial intelligence, especially deep learning models, significantly improves accuracy, efficiency, and scalability in dental identification, age estimation, and bite mark analysis, with performance often exceeding ninety percent under controlled conditions. Results further reveal that successful implementation depends on data quality, interdisciplinary collaboration, and institutional readiness, while challenges include ethical concerns, data limitations, and lack of standardized protocols. The study concludes that artificial intelligence has strong potential to transform forensic odontology practices and can serve as a strategic role model for institutional adoption, provided that technological integration is aligned with infrastructure, human resources, and governance frameworks. Implications extend to policy development, capacity building, and future research directions emphasizing real-world validation and sustainable implementation strategies in complex healthcare environments globally]]>
