In current education quality assessment, reducing complex educational processes to one-dimensional indicators that fail to reflect the full learning environment remains a key issue. To address this, a comprehensive approach is needed, combining pedagogical qualimetrics with fractal cluster analysis. This study develops a tool to enhance the accuracy, flexibility, and analytical depth of educational monitoring, considering academic performance dynamics, programme typology, and risk profiles. The methodology involved a literature review, classification of existing methods, and scenario modelling. The result is a system that integrates quantitative indicators with fractal features and data clustering, allowing for more nuanced assessment and personalised conclusions. The proposed model can inform new assessment standards during the digital transformation of education.