With currently deployed technologies for train completeness detection and positioning, it is not possible to reliably determine a train’s exact position and integrity within a block section. To enable advanced signaling concepts, a highly reliable train integrity (TI) monitoring technology is required. Although numerous TI technologies are currently under investigation, existing studies typically assess them individually, using only one or two criteria. This study presents the first comprehensive multi-criteria evaluation of key TI technologies using both an improved linear OPA and Fuzzy Z-OPA framework. Based on a literature review, eighteen TI-related technologies were identified and consolidated into eight representative TI alternatives, which were evaluated against eight criteria. The improved linear OPA model was first applied to establish rankings under crisp assumptions, after which the evaluation was repeated using Fuzzy Z-OPA to capture uncertainty in expert judgments. Due to its robustness in handling imprecision, the fuzzy-based results were used for the final analyzes. The results indicate that scalability, delays, energy utilization, and communication reliability are the most influential criteria in selecting TI alternative. Although the reliability and failure rate are widely recognized as safety–critical attributes, the literature review revealed that no measurable metrics exists for their systematic evaluation. To address this gap, this study derives and proposes corresponding evaluation metrics for the first time. The final ranking of TI alternatives identifies track-based train detection and transponder as the most suitable alternatives, while distributed sensing and Wireless Sensor Network (WSN) approaches show limited suitability for advanced signaling applications.