The building industry is facing increasing demands for sustainable and efficient maintenance practices, driven by advancements in Industry 4.0 technologies. Maintenance 4.0 emphasizes proactive maintenance strategies, including Condition-based Maintenance (CbM) and Predictive Maintenance (PdM), significantly enhanced by Digital Twin (DT) technology. DT enables the real-time monitoring, simulation, and optimization of building assets, offering substantial improvements in asset management, energy efficiency, and system longevity. However, integrating these technologies into the building industry's maintenance processes remains a challenge. This paper provides a comprehensive review of current research on DT-enabled Maintenance 4.0, presenting a conceptual framework that integrates enabling technologies and outlines their technological pipelines. It discusses the state-of-the-art methodologies, challenges, and future directions for the implementation of Maintenance 4.0 in the building sector, highlighting the potential of DT systems in optimizing maintenance strategies and enhancing decision-making. The study identifies key areas for further research, including data standardization, AI integration, and hybrid modeling approaches.