As human error has been recognized as one of the major contributors to accidents in safety-critical systems, there has been a strong need for techniques that can analyze human error effectively. Although many techniques have been developed so far, much room for improvement remains. As human error analysis is a cognitively demanding and time-consuming task, it is particularly necessary to develop a computerized system supporting this task. This paper presents a computer-aided system for analyzing human error in railway operations, called Computer-Aided System for Human Error Analysis and Reduction (CAS-HEAR). It supports analysts to find multiple levels of error causes and their causal relations by using predefined links between contextual factors and causal factors as well as links between causal factors. In addition, it is based on a complete accident model: hence, it helps analysts to conduct a thorough analysis without missing any important part of human error analysis. A prototype of CAS-HEAR was evaluated by nine field investigators from six railway organizations in Korea. Its overall usefulness in human error analysis was confirmed, although development of its simplified version and some modification of the contextual factors and causal factors are required in order to ensure its practical use. Crown Copyright (C) 2009 Published by Elsevier Ltd. All rights reserved.