Relevance. The research is relevant due to the potential of mathematical risk modeling in diagnosing corruption within the acquisition system. This approach is highly effective in identifying the causes and conditions of corruption, offering significant prospects for improving anti-corruption measures. Purpose. The study aims to comprehensively analyse both the normative and theoretical foundations of mathematical risk modeling in the acquisition system. The goal is to develop doctrinal proposals to enhance the current state of mathematical modeling in this context. Methodology. The authors used analysis, synthesis, formal-logical methods, system-structural methods, and mathematical modeling to examine Kazakhstan's anti-corruption regulations and establish legal grounds for diagnosing corruption risks. Results. The research presented an evidence-based proposal for the gradual implementation of mathematical modeling provisions in diagnosing corruption risks within the acquisition system, structured in two stages. It offered a critical analysis of theoretical developments on the subject, explored the functions of mathematical modeling in jurisprudence, and discussed their concepts and types. The study also developed a mathematical formula for calculating corruption risks and described its components. Conclusions. The study's findings include recommendations for developing mathematical formulas to diagnose corruption risks in the procurement system, highlighting the practical significance of the work. These recommendations provide valuable insights for improving anti-corruption measures through the application of mathematical risk modeling. Keywords: strategy; Kazakhstan Republic Law; cause and conditions of the crime; scientific program