<p>We provide a useful and effective method to visualize and graphically assess the multivariate normality of a dataset. The approach relies on a characterization of multivariate normal distribution, which states that the cumulant generating function is quadratic in its argument if and only if the distribution of the underlying random vector is multivariate normal. Thus, the approach is based on the collective evaluation of third and fourth order derivatives of the cumulant generating function, using which we define a function that can be plotted to visually evaluate the departures from multivariate normality.</p>