This paper designs a visual goodness-of-fit test based on the probability integral transformation of the residuals of an estimated model. We illustrate the method with histograms and correlograms of transformed series for different distributions of disturbances in simulated models. An application of the proposed test to the modeling of daily stock-market returns is also presented.