The book "Statistical Estimation for Truncated Exponential Families" offers a comprehensive examination of non-regular statistical estimation. It emphasizes the importance of distinguishing between regular and non-regular distributions by focusing on a specific family of distributions known as truncated exponential families. This family includes, among others, the truncated Pareto distribution, which is applied in various disciplines such as finance, physics, hydrology, geology, and astronomy. The work aims to present new insights into the maximum likelihood estimation of both the natural parameter and the truncation parameter, particularly when one of these parameters is considered a nuisance parameter. Additionally, a Bayesian approach to obtaining further information about the truncation is discussed. The clear explanations of the non-regular structure provide researchers and practitioners with a solid foundation for further studies and applications.