The cerebellum has a well-established role in locomotion control, but how the cerebellar network regulates locomotion behaviour is still not well understood. We therefore characterized the activity of cerebellar neurons in awake mice engaged in a locomotion task, using high-density silicon electrode arrays. We characterized the activity of over 300 neurons in response to locomotion, finding tuning to speed of locomotion, turning, and phase of the step cycle. We found that the cerebellar neurons we recorded mainly encoded information about future locomotor activity. We were able to decode the speed of locomotion with a simple linear algorithm, needing relatively few well-chosen cells to provide an accurate estimate of locomotion speed. Our observation that cerebellar neuronal activity predicts locomotion in the near future, and encodes the required kinematic variables, points to this activity underlying the efference copy signal for vertebrate locomotion.