<![CDATA[Hazard identification and risk assessment (HIRA) is a key element in occupational health and safety (OHS) and industrial safety systems, particularly in high-risk industrial sectors with complex processes and dynamic operations. Over the past decade, various methodological developments have been proposed, but their application remains scattered and not optimally integrated. This narrative review aims to synthesize and critically examine research findings related to the application of HIRA and risk assessment methods in the context of occupational and industrial safety and health. This study employed a narrative-review approach. A structured literature search was conducted through the ScienceDirect database for articles published between 2015 and 2025 via a combination of keywords related to hazard identification, risk assessment, occupational safety, and the industrial context. From the 2,093 publications obtained in the initial stage, a multistep screening process was conducted based on relevance, inclusion criteria, full-text evaluation, and conceptual assessment, ultimately yielding 15 core articles for the qualitative synthesis. The synthesis results revealed that the methodological depth of HIRA implementation significantly impacts the quality of OHS decision-making support. Hybrid methods (e.g., fuzzy Bayesian networks integrated with HFACS) demonstrated 15–30% higher accuracy in hazard prioritization than standalone qualitative matrices did. The effectiveness of the method is highly dependent on the system complexity, hazard characteristics, and maturity level of the organization. This narrative review demonstrates a paradigm shift from HIRA as an administrative obligation to HIRA as a strategic, risk-based tool to support OHS decision-making. An adaptive, integrated, and decision-oriented risk assessment approach provides a stronger foundation for developing an effective and sustainable safety management system.]]>
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