The process of moving the hand to a target in space involves a series of sensorimotor transformations that translate visual and other sensory information about the location of the target object and the limbs into a set of motor commands that will bring the hand to the desired position. Recent work at various laboratories has provided strong support for the hypothesis that the CNS learns and maintains internal models of sensorimotor transformations. An internal model is a neural system that mimics the behaviour of the sensorimotor system and objects in the external environment. Internal models enable the CNS to predict the consequences of motor commands and to determine the motor commands required to perform specific tasks. In this chapter, we first summarize recent computational, behavioural and neurophysiological studies that address the theoretical necessity of internal models, the locations of internal models, and the neural mechanism for acquiring internal models through learning. Then, we propose a new computational model of multiple internal models.