<p>This paper presents a Multi-Criteria Decision-Making (MCDM) framework that combines Yager aggregation operators with Complex T-Spherical Fuzzy Sets (CT-SFS) to tackle urban planning challenges. CT-SFS offers a two-dimensional evaluation model using amplitude and phase to represent Membership Grades (MG), Neutral Membership Grades (NG), and Non-membership Grades (NMG), enabling a deeper understanding of periodic and oscillatory behaviors compared to traditional T-Spherical Fuzzy Sets (T-SFS), which are confined to one-dimensional evaluation. In traffic management, for example, amplitude represents the green light phase duration, while phase captures timing offsets-both crucial for optimizing traffic flow in densely populated areas. The framework introduces two novel aggregation operators: the Complex T-Spherical Fuzzy Yager Weighted Average (CT-SFYWA) and the Complex T-Spherical Fuzzy Yager Weighted Geometric (CT-SFYWG), which are analyzed for properties such as idempotency, boundedness, and monotonicity, ensuring their reliability. By leveraging CT-SFS’s two-dimensional structure, the framework enhances uncertainty handling, improving precision in complex evaluations. The framework’s practical applicability is illustrated with a case study that prioritizes urban development initiatives in Chennai, India. Sensitivity and comparison analyses confirm the framework’s resilience and adaptability. The study’s conclusion highlights the framework’s potential for more efficient real-world urban planning decision-making. By discussing its contributions, consequences, limitations, and potential for further research, it establishes the foundation for future advancements in this field.</p>