This study introduces a Mitigation Ontology (MO) designed for the analysis of safety-critical systems. Recognizing the paramount importance of systematically addressing potential risks and hazards in complex systems, the proposed ontology serves as a structured framework for comprehensively modeling and analyzing mitigation strategies. Leveraging ontological principles, the framework enables a precise representation of safety-critical information, emphasizing the relationships and dependencies among various mitigation elements. To encapsulate the essence of safety-critical systems and support understanding of the mechanisms of situations, events, and associated hazards, we propose a hazard and mitigation domain ontology, i.e., the MO to provide a combined ontological interpretation of hazard and mitigation strategies. The MO facilitates a more thorough and standardized analysis of safety measures, contributing to enhanced understanding, communication, and implementation of mitigation strategies in software and hardware levels of safety-critical systems. The MO is grounded on Unified Foundational Ontology (UFO) and based on widely accepted standards, and scientific guides. We demonstrate our proposed ontology in the autonomous vehicle domain to check how it can help to analyze the safety of real-world safety-critical systems. Through the ontology instantiation process for a case study from the autonomous vehicle domain, we have verified that safety-critical related hazards, causes and consequences, and other entities contributing to hazards were well identified. we have seen that the MO offers a shared vocabulary that facilitates communication among diverse communities, preventing misunderstandings among engineers and stakeholders involved in safety-critical systems. Additionally, the conceptual model serves as a reference point for developers of safety-critical systems, enabling them to systematically extract and analyze safety requirements specifications and provide safety mechanisms.