Cities play a significant role on the fate of materials in economy-wide flows. Their sustainability is integral to the future of resource utilization. Circular city economies are recommended for the future of sustainable cities. Shifting towards a circular economy is challenging as urban metabolism is intertwined with city characteristics. The effectiveness of action plans is vital towards the shift through insight derivation of past city-level data. Rough set-based model can draw insights from city-level data in interpretable form, facilitating communication between analysts and city planners. This approach generates if-then rules based on the city-level data. This work generated 14 if-then rules from data of 100 cities using rough set theory. The model identified 5 relevant city characteristics from the 13 characteristics available from the data. The relevant characteristics are demographic, education, ease of doing business, income inequality, and tourism. The metric on waste management for cities was selected as the decision attribute of the model as it is the most relevant to circularity. The model attained a classification accuracy of 94 %. Specific if-then rules achieved coverage as high as 64 %, allowing ease of analysis. The rules suggest the level of development as the delineation between waste management system performances. The findings highlight the relevance of future studies on circular economy of developing countries. Results of this work provide insights on critical features that occur in more sustainable cities, which can be used to plan future circular city economies.