Distance measure is an essential tool that helps in assessing the similarity or dissimilarity between two p, q-quasirung orthopair fuzzy sets (p, q-QROFSs). It helps the decision-makers in more accurate data processing and decision-making in uncertain situations. This paper introduces a new method for measuring distance between p, q-QROFSs, with the goal of accurately differentiating between different entities in complex and unpredictable environments. Further, we check the validity of the proposed distance measure for p, q-QROFSs by analyzing other desirable characteristics. The proposed distance measure can address the limitations of existing distance measures for p, q-QROFSs, which are inadequate in accurately categorizing unknown patterns in comparison to known patterns. Finally, data experiments are carried out that validate the effectiveness of the proposed distance measure, leading to the conclusion that the proposed distance measure outperforms the existing ones.