Theoretical considerations and psychophysical studies of sensorimotor integration describe the dynamic regulation of behavior in terms of three computational building blocks: a controller (i.e., inverse model), a predictor (i.e., forward model) and a state estimator (e.g., Bayesian estimator). However, due to the complexity and concurrent engagement of these computations during natural movements, direct evidence that the nervous system establishes inverse and forward models remains elusive. We tackled this problem by designing a sensorimotor timing task in which the function of the inverse and forward models was simple and their deployment was segregated in time. Recording from the frontal cortex of monkeys performing this task revealed the differential contribution of the inverse and forward models to the regulation of the underlying neural dynamics. Our findings provide direct evidence that the nervous system establishes task-relevant internal models to perform Bayesian sensorimotor integration.