Staff risk analysis in the railway maintenance workplaces is a very complicated subject determined by numerous aspects including human error. Many risk assessment techniques currently used are comparatively mature tools. Howerver, in many circumstances, the application of these tools may not give satisfactory results due to the risk data incomplete or the high level of uncertainty involved in the risk data. This paper presents a methodology for staff risk assessment using fuzzy reasoning approaches (FRA), in particular, in the railway maintenance workplaces. The proposed method can evaluate qualitative and quantitative risk data associated with the railway maintenance workplaces in a uniform manner for staff risk analysis. Input parameters, probability of occurrence of hazardous events and their consequent severities in terms of membership functions, are used as inpurt information to analyse risks. The risk associated with the risk rules is then mapped back to the defined risk level expressions. The outcomes of the risk assessment are represented as the risk degrees and the defined risk categories of risk levels with a belief of percentage, which provide very useful risk information to risk analysts, project managers and site engineers. The proposed methodology permits risk analysts to assess the risks associated with the hazardous events directly using linguistic terms. This will provide railway risk analysts, managers and engineers with a method and tool to improve their safety management and set saftety standards. A case example on staff risk assessment at Victoria line depot is used to demonstrate the proposed approach. The result indicate that by using the proposed methodology risks associated with a railway maintenance workplace can be assessed effectively and efficiently. The proposed method could be transferred to other applications and used by other industrial companies who face to manage saftety and health on the construction sites.