Disaster can have a catastrophic consequence in dignified management of dead bodies and facilitate their identification. Human identification is the cornerstone of forensic science. Dental imaging, especially panoramic orthopantomogram (OPG), has become a promising alternative, because dental structures are unique in their anatomy and remain stable over time. The study seeks specific identifiers based on craniometric landmarks on mandible which are most neatly visible in panoramic radiographs. Objective of the study is to identify and annotate anatomical landmarks (mental foramen and inferior alveolar nerve canal) from OPG as reliable odontological biometric feature of human identification. To build an automated AI-based dental anatomical landmark detector that uses a convolutional neural network (CNN) to recognize landmarks and configure a fully automated identification system based on detection using a large dataset of panoramic OPG images. The technique combines linear and geometric form analysis to provide precise measurements. It employs generalized Procrustes analysis and Pearson’s correlation to achieve consistent and reliable outcomes. These results also indicate that image profiling using multiple landmarks can be helpful for forensic work across different clinical settings. The comparative analysis between the manual annotations and AI predicted outcome of 4.72 pixels suggests a very strong correlation across various selected anatomical landmarks show how important the mandible’s structure is for identifying people at crime scenes and how AI can make X-rays better for both health care and medico legal investigations.