Some power sectors face significant challenges, including aging infrastructure, frequent equipment failures, and high maintenance costs, which hinder reliable electricity supply. This study explores the application of Digital Twin (DT) technology for predictive maintenance in hydropower plants, aiming to improve operational efficiency, reduce unscheduled downtime, and enhance grid resilience. Using a quantitative approach, real-time and historical data from hydropower station were analyzed to assess the impact of DT integration. Results indicate that DT technology enables early fault detection, optimizes resource allocation, and reduces maintenance costs. DT technology enabled early fault detection, reducing unscheduled downtime by 20%. Maintenance costs decreased by 15% through optimized resource allocation. Asset lifespan improved by 10%, enhancing long-term sustainability. The study concludes that DT adoption can significantly improve the reliability and sustainability of power generation and distribution systems, offering a model for other critical infrastructure sectors