In information aggregation, a typical averaging mean called the partitioned dual Maclaurin symmetric mean (PDMSM) operator has drawn a lot of interest. All attributes are categorized into many partitions as a precondition for PDMSM, and attributes inside a partition are pertinent to other characteristics within the same group, whereas attributes situated in various groups are unrelated. On the other hand, no research on the partitioned dual MSM operator under Fermatean fuzzy set has yet been published. To bridge this gap, this study develops the FFPDMSM and FFWPDMSM operators with respect to FFNs and proposes a multi attribute decision making (MADM) framework employing PDMSM operator in Fermatean fuzzy environment. In the interim, a few theorems, properties and specific instances of the FFPDMSM and FFWPDMSM operators of FFNs have been examined. Lastly, a realistic numerical illustration is demonstrated to validate the proposed approach and to carry the sensitivity and comparative analysis.