<p>Numerous approaches have been employed to optimize traffic signal systems in response to rapidly increasing traffic volumes. However, the sheer variety of methods can sometimes overwhelm and confuse early career researchers seeking guidance. Traffic signal control relies on various criteria that guide method selection, broadly categorized into fixed specifications identified through empirical data and adjustable parameters that vary by context. Given this complexity, integrating a multicriteria decision-making (MCDM) framework is essential. This study proposes a fuzzy-TOPSIS-based framework -where TOPSIS stands for Technique for Order of Preference by Similarity to Ideal Solution - that integrates both fixed and adjustable evaluation criteria to rank traffic signal control methods based on situational needs. The approach serves as a decision support tool that accounts for uncertainty in expert judgment while ensuring a systematic and transparent method selection process. This framework evaluates various traffic signal control methods, taking into account both fixed and adjustable criteria, to identify the most suitable solution for a given case study. The proposed method not only simplifies the decision-making process, but also provides a structured and reliable tool for researchers and practitioners in the field of intelligent traffic management.</p>