Abstract: The risk analysis of rainfall-induced disasters along the railway can provide a reference for precise flood prevention for railway departments. Based on the daily precipitation data from national weather station along the Shuozhou-Huanghua railway from 1951 to 2022, this study used three distribution functions, Pearson III, Gumbel and Logarithmic normal distribution, to fit the recurrence period of annual maximum daily precipitation over the years along the railway respectively. The chi-square test was used to select the optimal fitting distribution model in different regions. Then the distribution characteristics of the maximum daily precipitation for different recurrence periods in each region along the Shuozhou-Huanghua Railway were obtained. Using the hourly precipitation data of the national meteorological stations from 2004 to 2023 and the meteorological stations deployed by the railway department from 2018 to 2023, the rainfall process and precipitation factors along the railway were counted. A total of 12 factors of rainfall process, including the annual average frequency and the extreme value of process precipitation, maximum hourly precipitation and maximum 24-hour precipitation that reaching the thresholds for patrol, speed limit and blockade warning respectively, were selected to construct the risk assessment index of rainfall-induced along Shuozhou-Huanghua Railway. Then the AHP-entropy weight method was applied to calculate the weight coefficient of each evaluation index factor. Finally, the hazard level of rainfall along Shuozhou-Huanghua Railway was obtained. The results show: The sections from Xibaipo Station to Sanji Station and Boye Station to Lixian Station along the Shuozhou-Huanghua Railway are the highest risk level of rainfall, while the sections from South of Shenchi Station to Dongye Station are the lowest risk level of rainfall, the assessment results are basically consistent with the distribution of maximum daily precipitation in different return periods.