TrueMortem is an AI-driven cause-of-death prediction and analysis system focused on identifying whether a person’s death was due to heart-related conditions. The project was developed in response to the growing need for data-driven support tools in forensic pathology, particularly in Sri Lanka, where standardized digital postmortem analysis is lacking. TrueMortem utilizes two distinct models trained on different data sources: a structured postmortem dataset manually curated from Kurunegala General Hospital, and a verbal autopsy dataset obtained from the PHMRC Gold Standard VA database. The postmortem model processes medical findings such as internal organ damage, external injuries, and demographics using machine learning algorithms. After experimenting with various models, Random Forest was selected for its superior performance, interpretability, and ability to handle missing data. The verbal autopsy model, designed to work with questionnaire-based data, uses an ensemble of Random Forest, SVM and LightGBM for improved accuracy. The system features a React-based frontend, a FastAPI backend, and a RASA-powered chatbot integrated with an LLM to answer user queries. An interactive dashboard presents prediction results, confidence scores, and feature importance using SHAP values for transparency. TrueMortem ensures data security, complies with ethical standards, and addresses legal requirements for sensitive medical data. While currently focused on heart-related deaths, the system is modular and scalable, paving the way for future expansion to other causes of death. It stands as Sri Lanka’s first AI-powered mortality analysis tool, supporting forensic experts and public health officials in making informed, evidence-based decisions.