<p>With intensifying global climate change, the frequency and intensity of extreme precipitation events continue to rise, posing a significant threat to railway system safety and stability. This study integrates historical records with systematically collected internet-based disaster reports to establish a comprehensive and long-term database of precipitation-induced railway disasters (PIRDs) in China. A systematic analysis is conducted to examine the spatiotemporal distribution patterns of these disasters and their impact on railway systems. The results indicate that PIRDs exhibit strong seasonality, with 83.8% of incidents occurring between June and August. Spatially, these disasters are concentrated in the southeastern coastal and central regions of China. The primary types of PIRDs include flooding (34.7%) and geological (46.5%) disasters, with severe damage observed in track subgrades and slopes. Furthermore, this study examines key environmental factors influencing PIRDs, such as elevation, slope, soil type, and land use type, providing valuable insights for disaster prevention. By analyzing the impact of precipitation on different time scales, a predictive model for PIRDs is developed, and risk thresholds are established to assess the probability of disaster recurrence under future precipitation patterns. The model calculates the relative risk index for affected railway sections across China in 2023 and predicts disaster risks under future precipitation conditions for selected representative sections. The findings demonstrate that the proposed model effectively quantifies the relationship between precipitation characteristics and railway disaster risks. This study provides a scientific basis for railway disaster prevention in China and offers transferable insights for railway risk management in other regions.</p>