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Ensuring the sustainability of renewable energy transition logistics relies on the successful management of various risk factors. In this study, the evaluation of risk factors related to the implementation of green logistics (GL) in renewable energy transition is carried out. To address the limitations of conventional risk priority number (RPN), a modified Failure Mode and Effects Analysis (FMEA) approach that incorporates decision-makers'(DMs) perspectives DMs using a Spherical Fuzzy Set (SFs) is proposed. The use of SFs helps to mitigate the vagueness and imprecision inherent in DMs' opinions. The proposed framework leverages the Spherical Fuzzy Best-Worst Method (SF-BWM) to determine criteria weights and combines SFs with the Combinative Distance-Based Assessment (SF-CODAS) method to rank the recognized risk factors. The resulting critical risk factors provide valuable insights for effective risk management in GL implementation. The effectiveness of the proposed approach was validated through a comparison of its results with those obtained from other MCDM methods, as well as through conducting sensitivity analysis. The outcomes of this evaluation provide strong evidence of the efficacy of our proposed method.