This book provides the latest advances in the theory and practice of Marshall-Olkin family of distributions. In recent years, these distributions have become more widely used in statistical practice, as they allow for the description of intriguing aspects of stochastic models such as non-exchangeability, tail dependencies, and the presence of a unique component. This distribution has been broadly applied to the description of real-world phenomena and the modelling of data in very many disciplines, including insurance, economics, finance, engineering, biology, industry, and medical sciences. This book offers a recent update, essential properties, generalizations, and applications of the Marshall-Olkin family of distributions. It is recommended for researchers working in applied probability and statistics, as well as for practitioners interested in the use of stochastic models in different areas.