In recent decades, uncontrolled, scattered, and unregulated development in urban outskirts has increasingly become a dominant pattern of physical growth in cities. This pattern, commonly referred to as urban sprawl, is characterized by dispersed development in peripheral areas and relatively low-density land-use patterns. The expansion of urban activities into peripheral areas has created various challenges for urban development and management and has consequently attracted considerable attention in urban planning studies. In response to these challenges, various case-specific and localized solutions have been proposed to control the negative consequences of dispersed development. Subsequently, smart growth emerged as a comprehensive approach to addressing dispersed and low-density urban expansion. Smart growth emphasizes a more efficient spatial organization of urban activities and seeks to promote development patterns that are more consistent with the principles of sustainable and efficient urban development. Accordingly, numerous studies have investigated the application and assessment of smart growth principles in different urban contexts. Based on this background, the present study aims to examine smart growth indicators in urban districts and subsequently rank these districts according to the selected indicators. In this regard, the main research question is: What is the status of smart growth indicators in the urban districts of Shahroud, and what ranking do these districts obtain based on these indicators? Shahroud City, consisting of seven urban districts, was selected as the case study. During the past two decades, Shahroud has experienced dispersed development, particularly in its southern areas. Therefore, assessing the existing spatial conditions of its urban districts in terms of smart growth indicators can provide a basis for identifying differences among districts and determining their relative levels of smart growth. According to the research methodology, 37 sub-indicators representing different aspects of smart growth were examined. These sub-indicators were classified into four main dimensions: socio-economic, physical and land-use, environmental, and accessibility. The required data were obtained from available statistical and planning sources related to Shahroud City. To determine the relative weights of the indicators, the entropy method was employed. This method was used to determine the importance of the indicators based on the information contained in the available data. Subsequently, the TOPSIS model was applied to evaluate and rank the seven urban districts of Shahroud according to their level of conformity with smart growth characteristics. The results provide a comparative assessment of the spatial differences among the districts across the four dimensions of smart growth. The findings indicate that District 2 of Shahroud achieved the highest rank in the socio-economic dimension, while District 3 obtained the highest rank in the physical and land-use dimension. District 1 achieved the highest rank in both the environmental and accessibility dimensions. These findings demonstrate that the urban districts do not have the same level of conformity with the different dimensions of smart growth and that their strengths and weaknesses vary across the examined dimensions. In addition, the results of multiple regression analysis showed that the environmental dimension and its related sub-indicators had the greatest influence on the formation and spatial development of Shahroud City based on the smart growth pattern. Therefore, the findings emphasize the importance of environmental indicators in explaining the spatial conditions of smart growth in the city and can contribute to a more informed assessment of urban districts and the identification of priorities for urban development and management.