This book details how artificial intelligence and other informatic methods can be applied to the field of tribology. Using problems often found within tribological condition monitoring, behaviour prediction, system optimization and mechanism analysis, the book covers methods used such as Artificial Neural Networks (ANN). Including case studies throughout, the book offers an accessible introduction to tribological research, beginning with background on the theory behind tribo-informatics, and updates in the latest technology. It describes how to establish a tribo-informatics database, methods through which to express tribo-systems such as Artificial Neural Networks (ANN), Support Vector Machines (SVM), K-Nearest Neighbor (KNN), and Random Forest (RF), and its applications. It can be used in state monitoring, behaviour prediction and system optimization. Through case studies, practical examples of how tribo-informatics can be implemented are shown throughout various industries. This book will be of interest to students and researchers in the field of tribology, friction, wear and artificial intelligence.