Bridges are an essential component of the transportation system and safety and sustainability of bridges are critical for the efficient operation thereof. Due to scarcity of resources, an economical way should be determined to design and maintain bridges and the transportation system in general. Reliability indexes are widely used in the analysis of these concepts within a semi-probabilistic approach. However, advances in computer technology allow implementing a fully-probabilistic approach. This study represents a simulation-based reliability analysis of steel girder bridges in the railway lines. Statistical parameters of the bridges are determined both analysing the existing body of knowledge available in the literature and conducting specimen tests. The Bayesian approach is used to update the statistical properties of the steel material. Basic Monte Carlo Simulation (MCS) is used to simulate the load and resistance of the bridge. The reliability of the bridges is determined according to their ultimate limit states and statistical load distribution. By using simulation, the consistency of the log-normal marginal distribution obtained is analysed herein.