In recent years, the application of machine learning tools to legally relevant tasks has become much more prevalent, and the growing influence of AI in the legal sphere has prompted the profession to take more of an interest in the explainability, trustworthiness, and responsibility of intelligent systems. This book presents the proceedings of the 32nd International Conference on Legal Knowledge and Information Systems (JURIX 2019), held in Madrid, Spain, from 11 to 13 December 2019. Traditionally focused on legal knowledge representation and engineering, computational models of legal reasoning, and analyses of legal data, more recently the conference has also encompassed the use of machine learning tools. A total of 81 submissions were received for the conference, of which 14 were selected as full papers and 17 as short papers. A further 3 submissions were accepted as demo presentations, resulting in a total acceptance rate of 41.98%, with a competitive 25.5% acceptance rate for full papers. The 34 papers presented here cover a broad range of topics, from computational models of legal argumentation, case-based reasoning, legal ontologies, and evidential reasoning, through classification of different types of text in legal documents and comparing similarities, to the relevance of judicial decisions to issues of governmental transparency. The book will be of interest to all those whose work involves the use of knowledge and information systems in the legal sphere.