To ensure the optimal performance of prestressed concrete bridges, a seamless flow of data from the design phase through to operation is crucial. This study proposes the adoption of digital engineering models for both individual prefabricated bridge members and the fully assembled structure, facilitating comprehensive information delivery throughout the bridge’s lifecycle. It underscores the importance of documenting variations in material properties and construction stages, culminating in the establishment of a baseline model upon bridge completion, grounded in actual rather than assumed design data. The ongoing collection of inspection data during the bridge’s operational phase enables continual update of this model, enhancing the reliability of performance assessments. A pivotal advancement is the development of a conceptual digital twin model, enriched by aggregated data from analogous structures, which heralds a new era in predictive analytics for bridge performance. The application of this model to an expressway bridge illustrates its potential to revolutionize bridge engineering by enabling proactive maintenance and management strategies. This paper not only details the framework of this innovative digital twin model but also highlights its practical implications, marking a significant leap forward in the field of civil engineering.