The result of a multiobjective evolutionary optimization is an efficient solution set surrounded by other candidate solution points. To choose a final solution, we can perform a sensitivity study. Applying this methodology, disturbances that occur in real-world design problems are not neglected. This paper presents an easy way to perform the sensitivity analysis directly from the data generated from a multiobjective stochastic optimization process. No additional function evaluation is required. As an example, we have solved some optimization problems concerning electromagnetic devices.