The book "Handbook of Mixture Analysis" is a collection of peer-reviewed articles featuring several statistical data analysis methods based on mixture models and their applications in scientific domains such as data mining, machine learning, physics, mechanical engineering, signal processing, economics, cosmology, computational medicine, and more. This book covers several aspects of mixture analysis and variety of models such as the Gaussian Mixture Model (GMM), Dirichlet processes Mixture Model (DMM), Poisson Mixture Regression Model (PMRM), Hierarchical Gamma Mixture Model (HGMM), Quadratic Mixture Model (QMM), K-fold Mixture Model (KMM), Finite Mixture Model (FMM), and Multi-partitions Subspace Mixture Model (M-SMM).