The future of smart cities in the era of digital transformation is moving towards becoming “intelligent, predictive, and self-organizing” entities in which the boundary between physical space and digital layers is completely blurred using digital twin technologies and the Internet of Things. In this vision, urban management changes from a traditional and reactive approach to data-driven and predictive management, in which artificial intelligence analyzes urban flows to enable real-time management of traffic, energy, and resources. Also, by integrating concepts such as metaverse and mixed reality, citizens’ interaction with the urban environment will transform from a simple experience to an immersive and personalized experience, the ultimate goal of which is to improve the quality of life and achieve environmental sustainability. The purpose of the present study is to model futuristic smart cities in the era of digital transformation, case study: Tehran metropolis. In this study, the ISM model was used. This research is applied-theoretical in terms of purpose and descriptive-analytical in terms of method. The required information and data were collected through library and field methods. The acceleration of digital transformations in modern urban planning requires system models to manage the complexities of metropolises such as Tehran in order to provide a platform for the realization of sustainable smart cities. The purpose of this research is to analyze the structure and explain the interrelationships between key components in the modeling of Tehran's urban smartization using "Interpretive Structural Modeling (ISM)" method. In this study, by identifying and screening effective indicators in the infrastructural, governance, technological, and social dimensions, a hierarchical pattern of causal relationships between variables has been extracted in order to determine the prioritization of strategic actions future this metropolis.