Modelling the control of locomotor movements can take place at many different levels and represent gaits of different animal species. In many cases, these models attempt to capture the theoretical constructs for generating rhythmical motor patterns gained from neurophysiological studies. This chapter examines the use of artificial neural networks to gain insights into the control of walking movements. Two models discussed simplify the pathways and structures responsible for forming these fundamental cyclical movements, and capture the global transformations between intended goals and action. The use of computational models permits researchers to address certain questions that cannot be empirically tested using current experimental techniques.