Human error and degraded human performance are associated with more than 80% of all railway accidents worldwide. Research on human performance and human reliability has highlighted the importance of the contextual factors associated with human errors, known as performance shaping factors (PSFs). A major shortcomings of current Human Reliability Analysis techniques, which employ qualitative and quantitative methods for assessing the human contribution to risk, lies with their little capability to model the dependencies among PSFs and to quantify their impact on human performance. This paper presents a novel approach to assess human performance accounting for the dependencies among the relevant PSFs, referred to as Human Performance Railway Operational Index (HuPeROI). The HuPeROI is developed on the integration of the Analytic Network Process and Success Likelihood Index Methodology, using the insights of 52 front-line, managerial and human factors railway personnel, and was demonstrated in three different types of railway operations: regional, high-speed and underground. Findings show that the HuPeROI can be efficiently used to assess operators’ performance as function of the quality of the relevant R-PSFs. Regulatory bodies and other stakeholders can implement the framework within their safety management systems to improve safety of railway operations.