The fundamental and applied foundations of the modern theory of probabilistic modeling of real processes and phenomena are presented. The main attention is paid to the problem of mathematical assignment and classification of real experiments, intuitive concepts and formalization of permissible, elementary and observed outcomes, construction of set-theoretic and probabilistic models, functional and numerical characteristics of outcome meters of statistically stable experiments.