Bridges are critical components of road infrastructure, and it is of paramount importance that they are maintained in an optimal state in order to ensure public safety and the continuity of transportation services. The recent collapse of the Morandi Bridge in Genoa, Italy, has highlighted the critical necessity for accurate assessment and monitoring of bridge conditions in order to prevent catastrophic failures. An accurate comprehension of the current condition and actual behavior of bridges is indispensable for the formulation of effective maintenance strategies and the prevention of critical failures. While the Finite Element Method (FEM) improves the accuracy of structural safety assessments, there are numerous uncertainties and assumptions associated with the implementation of numerical models. Consequently, numerical results require validation through experimental measurements. This thesis aims to develop and apply specific model updating strategies based on ambient vibration testing (AVT) for multiple purposes, including reducing modeling uncertainties, detecting potential damage, and assessing the effectiveness of structural reinforcement interventions. AVT has been demonstrated to be an effective technique for capturing the true dynamic behavior of structures without disrupting traffic flow, thereby providing crucial data for the model updating process. By integrating AVT-derived experimental data with precisely calibrated Finite Element (FE) models, the research seeks to enhance the accuracy of bridge safety evaluations. The findings demonstrate that this integrated approach significantly improves the understanding of bridge structural behavior. This improved insight supports informed decision-making in bridge management and maintenance, thereby contributing to increased public safety and the reliability of transportation services.