Mixture analysis is very active research topic in statistics and machine learning. It is a good timing for a Handbook to present a broad overview of the methods and applications, suitable for graduate students and young researchers new to the field. This Handbook is divided into two main parts; the first part covers all the methods, with illustrative examples and guidance on computing where appropriate; and the second part includes some more advanced methodological topics, and a series of case studies presenting applications of mixture analysis in a number of fields, including genomics, medicine, economics, finance and more.