Kolmogorov's Probability Theory is a mathematical framework for understanding randomness and uncertainty. Developed by Andrey Kolmogorov in the 1930s, it formalizes probability through a set of axioms. These axioms define probability as a measure that assigns values between 0 and 1 to events, where 0 indicates impossibility and 1 indicates certainty. The theory also introduces concepts like sample spaces and events, allowing for the systematic analysis of random phenomena. By using this framework, researchers can model real-world situations, make predictions, and quantify risks in various fields, including statistics, finance, and science.