The evolving complexity of urban environments necessitates advanced planning strategies that align technological innovation with ecological sustainability. This study introduces a fuzzy logic-based decision-support framework for evaluating urban sustainability by integrating components of smart and green architecture. The proposed model utilizes a Fuzzy Inference System (FIS) to assess four key input variables: Energy Efficiency (EE), Green Infrastructure Level (GIL), Environmental Impact (EI), and Smart Technology Integration (STI). Each parameter is modeled using triangular membership functions and analyzed through a set of expert-informed fuzzy rules. The outcome is a Sustainability Score (SS) ranging from 0 to 100, classified into Poor, Fair, or Good categories. This fuzzy-based approach captures the nonlinear, ambiguous relationships between critical sustainability factors and enables partial truth evaluation, making it well-suited for real-world urban scenarios. The model's ability to combine data-driven insights with interpretability provides urban planners and policymakers with a flexible tool for balancing ecological priorities with digital transformation. Simulation results demonstrate the model’s capacity to reflect diverse urban configurations and guide decision-making toward more resilient and energy-efficient city planning. By embedding smart and green architectural principles into a unified framework, the study contributes to the development of intelligent, sustainable urban systems.