Railway infrastructure maintenance is essential in implementing the transportation system. Most of these railway bridges have suffered gradual deterioration over time. Predictive structural health monitoring (SHM) is required by installing instrumentation sensors on railway bridges to determine the condition of the railway bridge infrastructure at the site. This research aims to analyze and assess the existing condition of steel railway bridges to understand the load-deformation characteristics, bearing capacity, and dynamic response of the structure. This paper describes a valuable method for assessing the condition of steel railway bridges during operation. This paper presents a direct analysis of the steel railway bridge structure, with a span of 40.00 meters, a width of 4.40 meters, and a height of 6.60 meters. The steel structure railway bridge is modeled in 3D in detail, and numerical analysis is carried out using finite element analysis based on input parameters obtained from manual field measurements and instrumentation sensors. The expected result of the development of this SHM System is to know the performance of the steel railway bridge structure in real-time via the dashboard display. The results showed that the carrying capacity of the railway bridge was in a relatively safe condition. This case study may help practice engineers and researchers in future research. It can be a valuable reference for future research in developing and applying such a system to a typical case.