'Bayesian Networks and Probabilistic Inference in Forensic Science' provides a unique and comprehensive introduction to the use of Bayesian networks for the evaluation of scientific evidence in forensic science. Includes self-contained introductions to both Bayesian networks and probability. Features implementation of the methodology using HUGIN, the leading Bayesian networks software. Presents basic standard networks that can be implemented in commercially and academically available software packages, and that form the core models necessary for the reader´s own analysis of real cases. Provides a technique for structuring problems and organizing uncertain data based on methods and principles of scientific reasoning. Contains a method for constructing coherent and defensible arguments for the analysis and evaluation of forensic evidence. Written in a lucid style, suitable for forensic scientists with minimal mathematical background. Includes a foreword by David Schum.