Gathering information from a real-life scenario is a very difficult process due to involvement of the multiple criteria and human opinion. A complex Pythagorean fuzzy set (CPyFS) is an interesting tool to deal with uncertainty while gathering information from human opinion involved in real-life scenarios. But, the aggregation of the information gathered by CPyFS becomes very hectic. Several aggregation operators (AOs) aggregate the information in the form of complex Pythagorean fuzzy values (CPyFVs). However, they lack the prioritization of attributes according to their weights. In this article, an interesting new class of AOs including complex Pythagorean fuzzy (CPyF) prioritized averaging operator (CPyFPAO) and CPyF prioritized geometric operator (CPyFPGO) is introduced. Basic and necessary properties of the introduced AOs are observed. Furthermore, the case study is discussed where the introduced AOs are applied to seek the most suitable optimized site for starting a pilot health project with the help of the multi-attribute group decision-making (MAGDM) process. The results obtained from all proposed AOs are analyzed and compared with some existing AOs. All the analyses are explained with the help of the tabulated data and graphs.