This case study highlights advanced bridge monitoring using strain sensors and a digital twin model. A prestressed concrete railway bridge developing cracks was instrumented with electrical and optical strain gauges. Real-time data fed a digital twin, revealing stress patterns, crack behavior, and potential failure zones. This approach enables predictive maintenance, early damage detection, and longer bridge lifespan, moving from reactive inspection to proactive, data-driven management.