<p>Frank t-norms and t-conorms, which are flexible and general, are crucial for information fusion. Additionally, the Maclaurin symmetric mean operator, an extension of various mean operators, takes into account the link between multi-criteria arguments, particularly in multi-attribute group decision-making. The objective of this paper is to develop multiple aggregation operators for the spherical fuzzy set framework using the Frank t-norms and t-conorms approaches. Additionally, the study aims to apply the newly developed aggregation operators in the multiple attribute decision making process. First, the definition of the Maclaurin symmetric mean utilizing the Frank t-norms and t-conorms in the setting of spherical fuzzy values in order to use the multi-attribute group decision-making method is given. Next, suggested spherical fuzzy Frank weighted Maclaurin symmetric mean and spherical fuzzy Frank Maclaurin symmetric mean aggregation operators. The fundamental characteristics of these aggregation operators are then listed. Subsequently, a proposal is put forward that considers the utilization of the newly developed assortment of aggregation operators. Furthermore, the multi-attribute group decision-making problem is addressed by including newly specified operators, which are then applied in a case study that assesses the effectiveness of artificial neural networks. This study also discusses how these aggregation operators’ behavior can vary depending on how sensitive metrics are interpreted.</p>