This study provides a methodology to estimate the probability of exceeding different performance levels in reinforced concrete (RC) bridges, taking into account the cumulative damage caused by earthquakes, corrosion and scour over time. The methodology utilizes a stochastic framework to model the occurrence and intensity of earthquakes and scour, which allows for a probabilistic assessment of bridge performance under several conditions. The occurrence of earthquakes and scour are represented by a stochastic Poisson process. Corrosion, which is triggered by exposure to chloride ions, is characterized by a gradual decrease in the cross-sectional area of the steel reinforcement. The corrosion effect considers different stages of corrosion such as time of initiation, beginning of cracking and evolution of damage due to the reduction of reinforcement steel diameter. Scour and fill processes are analyzed within a one-dimensional stochastic framework. The proposed methodology ensures a comprehensive consideration of the various sources of uncertainty that can potentially impact scour and fill outcomes. Monte Carlo simulation is used to generate sequences of hazards and evaluate their combined impact on bridges. The model explicitly incorporates the variability inherent in material manufacturing processes and construction procedures as well as the occurrence of scour and earthquakes, recognizing the potential influence of these factors on the behavior of system bridges. The probability of exceeding different performance levels is estimated at specific time intervals such as 0, 50, and 75 years after the bridge system construction. The applicability and effectiveness of the proposed methodology are showcased through a RC bridge situated in Acapulco, Guerrero, Mexico. The bridge system is designed to comply a performance level equal to 0.2%. The proposed methodology can assist bridge owners and engineers in making informed decisions regarding maintenance, repair, and retrofitting strategies. The quantification of bridge fragility over time allows to prioritize interventions and optimize the allocation of resources to improve bridge safety.