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Stochastic Processes is a category of books focused on the mathematics and applications of systems that evolve randomly over time. Titles typically cover foundational models such as Markov chains, Poisson and renewal processes, and branching processes, as well as advanced topics like Brownian motion, martingales, stochastic calculus, and diffusion processes. Many works blend rigorous theory with modeling, simulation, and statistical inference, addressing areas such as time series, queueing, reliability, control, signal processing, and Monte Carlo methods. Applications span finance, engineering, computer science, operations research, biology, and the social sciences, and the category includes introductory textbooks, problem-driven guides, and research monographs for students, practitioners, and researchers.

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