Maritime accidents remain a concern in our society despite of the continuous improvement on safety measures. With the aim to contribute to current safety measures, this paper proposes to utilise the Safety Human Incident & Error Learning Database (SHIELD) Human Factors (HF) Taxonomy, which was developed in the context of the European Union SAFEMODE project, in line with the key components of NASA-HFACS, HERA, and Reason’s Swiss Cheese Model. SHIELD HF Taxonomy aims to identify active and latent failures within an organisation that contributed to an accident or incident. The goal of SHIELD HF Taxonomy is not to attribute blame; it is to understand the underlying causal factors that lead to an accident. Finally, SHIELD HF Taxonomy is demonstrated on a maritime accident collision to identify the main accident contributors.