Artificial intelligence (AI) technologies have begun to be used more frequently in forensic sciences, just as in every other field of medicine, and have become part of research topics. This study aims to conduct a comprehensive bibliometric analysis to systematically examine publication dynamics, collaboration networks, citation patterns, and thematic trends of AI in forensic sciences. A comprehensive literature search was conducted using the keywords "forensic medicine," "forensic sciences," "forensic pathology," autopsy, "artificial intelligence," "deep learning," and "machine learning" and analyzed using R Bibliometrix and VOSviewer software. The analysis identified 3434 authors, 8372 keywords, and 6276 references across 730 articles. A publication growth rate of 24.16% and international collaboration rate of 28.77% were observed. The United States emerged as the most productive country. The leading institutions were University of California and Shanxi Medical University. Research trends concentrated on diagnosis, bone age estimation, and forensic odontology. Publications appeared predominantly in high-impact journals including Forensic Science International and Nature Communications. AI and machine learning research in forensic sciences has experienced rapid growth. Although these technologies offer substantial potential to enhance accuracy, efficiency, and standardization in forensic investigations, critical challenges such as model interpretability and ethical considerations require further attention for future implementation.