<p>Spherical fuzzy sets are a recent advancement in fuzzy set theory, specifically developed to manage multi-criteria decision-making (MCDM) problems under conditions of vagueness, imprecision, and uncertainty. Aggregation operators play a pivotal role in practical decision-making, as they enable the integration of diverse expert judgments into a unified assessment. To enhance this capability, this study introduces three novel harmonic mean aggregation operators under spherical trapezoidal fuzzy numbers: the spherical trapezoidal fuzzy weighted harmonic mean (STraFWHM), the spherical trapezoidal fuzzy ordered weighted harmonic mean (STraFOWHM), and the spherical trapezoidal fuzzy hybrid harmonic mean (STraFHHM). Additionally, a spherical trapezoidal fuzzy best–worst method (STraF-BWM), supported by a nonlinear optimization model, is proposed to determine optimal fuzzy weight coefficients. Formal definitions and theoretical properties of the proposed operators are provided, followed by the application of the ordinal priority approach (OPA) to calculate the objective weights of experts and criteria. The STraF-BWM is further utilized to determine expert position weights, contributing to more robust and accurate decision outcomes. The effectiveness of the proposed methodology is demonstrated through a real-world case study involving the selection of an electric vehicle charging station location. Comparative analysis confirms the advantages of the proposed aggregation operators over existing methods in handling complex MCDM problems under uncertainty.</p>