In the vast expanse of scientific literature, determining which researchers have made the most significant contributions to their field is essential. However, the scientific community lacks a standardized set of criteria for identifying impactful researchers. Existing platforms, like Google Scholar, Semantic Scholar & Web of Science, provide useful metrics like total publications, citation counts, and h-index, but no universally accepted framework exists to comprehensively evaluate a researcher’s true impact. This study proposes a novel framework for identifying impactful researchers within the computer science domain. The framework integrates 64 distinct quantitative parameters across categories such as citation-based, publication-based, author-count-based, and age-weighted metrics to evaluate researchers’ contributions. Unlike traditional methods that focus on individual indicators, our framework provides a comprehensive evaluation model that considers multiple factors simultaneously. The parameters were selected based on their importance scores, determined by their ability to classify awardees and non-awardees. Experiments were performed on a balanced dataset comprising 600 awardees and 600 non-awardees, yielding classification accuracies ranging from 57% to 78% in recognizing influential researchers. The top-ranked features from each parameter category effectively promoted 50% to 55% of awardees into the top 100 researcher rankings. These findings offer a robust tool for academic institutions and organizations seeking to identify impactful researchers. The proposed framework enables more objective evaluation and provides actionable insights for individual researchers striving for recognition and influence in their field.