The railway system plays a crucial role in a nation's economy and society, extending beyond mere transportation. In earthquake-prone regions like Razavi Khorasan in Iran, railway infrastructure is highly vulnerable to natural disasters, which can severely disrupt train operations. Ensuring the safety of critical infrastructure, including stations, bridges, tunnels, and railway lines, is essential for maintaining operational integrity and public safety. This study evaluates and prioritizes seismic retrofitting measures for railway infrastructures in Razavi Khorasan. The fuzzy Delphi method is used to gather expert opinions, while the Fuzzy VIKOR method facilitates the prioritization process. Key assessment criteria include seismic intensity potential, vulnerability potential of the zone in terms of distance from the fault, the degree of criticality of the infrastructure in terms of the possibility of continuing transportation operations and the current state of the infrastructure in terms of the state of retrofitting against seismic hazards. The findings reveal critical railway segments that require immediate retrofitting interventions and highlight overall vulnerabilities within the system. This paper underscores the effective application of fuzzy logic methodologies in complex decision making scenarios, offering actionable recommendations to enhance the seismic retrofitting of railway infrastructures.