This comprehensive bibliometric study examines the integration of Digital Twin (DT) technology in Smart Cities, focusing on its applications, challenges, and future directions. The study analyzes over 4,220 articles from the Web of Science database, exploring unique aspects such as datasets, platforms, and performance metrics. Key findings include publication trends, prolific authors, and thematic clusters, highlighting the importance of DT in urban applications. The paper discusses the role of DT in various sectors, including energy management, traffic management, environmental monitoring, and public safety. It also addresses challenges and limitations, presenting case studies of successful implementations. The study emphasizes the integration of DT with Machine Learning and IoT, and the evolving role of policy and governance in DT development. The research contributes to a deeper understanding of DT technology in Smart City development, setting a new benchmark in scholarly research.This comprehensive bibliometric study examines the integration of Digital Twin (DT) technology in Smart Cities, focusing on its applications, challenges, and future directions. The study analyzes over 4,220 articles from the Web of Science database, exploring unique aspects such as datasets, platforms, and performance metrics. Key findings include publication trends, prolific authors, and thematic clusters, highlighting the importance of DT in urban applications. The paper discusses the role of DT in various sectors, including energy management, traffic management, environmental monitoring, and public safety. It also addresses challenges and limitations, presenting case studies of successful implementations. The study emphasizes the integration of DT with Machine Learning and IoT, and the evolving role of policy and governance in DT development. The research contributes to a deeper understanding of DT technology in Smart City development, setting a new benchmark in scholarly research.