This text discusses the software technique of load balancing in distributed memory message-passing parallel computers, also called multicomputers. It presents a comprehensive treatment of the subject using rigorous mathematical analyses and practical implementations. The focus is on nearest-neighbour load balancing methods in which every processor at every step is restricted to balancing its workload with its direct neighbours only. Nearest-neighbour methods are iterative in nature because a global balanced state can be reached through processors' successive local operations. Since nearest-neighbour methods have a relatively relaxed requirement for the spread of local load information across the system, they are flexible in terms of allowing one to control the balancing quality, effective for preserving communication locality, and can be easily scaled in parallel computers with a direct communication network. Load Balancing in Parallel Computers: Theory and Practice serves as an excellent reference source and may be used as a text for advanced courses on the subject.