Digital Twin technology is transforming public transportation by creating real-time virtual replicas of transit networks to optimize routes, reduce congestion, and enhance operational efficiency. This study explores how AI-powered digital twins integrate real-time data to predict traffic patterns, improve passenger flow, and enable predictive maintenance, ensuring reliable and cost-effective transit. While challenges like cybersecurity risks and implementation costs exist, integrating digital twins with AI, IoT, and 5G is shaping the future of smart, sustainable, and highly efficient urban mobility.