<p>Waterflooding stands as a primary technique for oilfield development. However, most oilfields have entered the (ultra-)high water-cut stage, which makes improving waterflooding performance in such oilfields a globally significant research focus. Establishing a comprehensive evaluation model, methodology, and technical framework for oilfield development performance scientifically is therefore particularly critical. It also involves identifying key breakthroughs to boost recovery efficiency and proposing adjustment measures to tap reservoir potential. This study employs systems analysis and data mining to evaluate waterflooded reservoir parameters. It covers four key dimensions: reservoir characteristics, engineering operations, wellsite management, and production economics. A combined subjective–objective approach identifies development-critical indicators that are mutually independent. Multiple data mining algorithms reduce human bias and the inaccuracies of single-algorithm evaluations. Hierarchical clustering screens indicators closely linked to waterflooding performance. It also determines their weighting coefficients. Theoretical principles, statistical patterns, and technical requirements are converted into quantitative feature descriptors. These descriptors help establish evaluation criteria for each parameter. By calculating reservoir composite scores, the study provides a systematic method to assess waterflooding effectiveness. It comprehensively considers factors influencing oilfield development performance. It also analyzes intrinsic relationships among evaluation indicators and reveals core mechanisms governing development effectiveness. These findings offer essential insights for optimizing oilfield development strategies.</p>