Pythagorean fuzzy set theory, an extension of the intuitionistic fuzzy set, provides a powerful capability to more efficiently model uncertain and vague concepts. Aggregation operators play a significant role in the information aggregation collected from various sources to obtain a single representative value. However, the existing confidence levels based on Pythagorean fuzzy aggregation operators have some drawbacks that make them irrelevant to use in practical situations. This paper presents a new advanced confidence levels Pythagorean fuzzy weighted average \((Adv-CLPFWA)\) operator to aggregate a finite collection of Pythagorean fuzzy numbers with their corresponding confidence levels. Some desirable properties of the \(Adv-CLPFWA\) operator are discussed. Finally, a multiple–attribute group decision-making (MAGDM) method based on the \(Adv-CLPFWA\) operator has been formulated and demonstrated with an example to validate its effectiveness.