The buckling behavior of structures is highly sensitive to imperfections, i.e., deviations from the geometry and material properties of the ideal structure. In this paper, an approach is presented in which the effects of spatially varying fiber misalignments in composite structures are assessed through random field analysis and are subsequently used to improve the structure while simultaneously making it more robust to fiber misalignments. Effects of misalignments are quantified by applying random fields on the structure, which represent fiber misalignments. Using analyses of the effect of the random local stiffness changes due to fiber misalign- ments, a pattern of the relative influence these local changes have on the buckling load is created. By applying a small change to local fiber orientation corresponding to this pattern to the original structure, the performance of the design is improved. Additional stochastic analyses are performed using the improved design, reanalyzing the effects local fiber misalignments have on the structural performance and the subsequent changes in robustness. Stochastic results show an overall increase in the mean buckling load and a reduction in the coefficient of variation in the analysis of the perturbed structure. The approach is applied to a composite panel exhibiting asymmetric post‐buckling behavior, i.e., having an unstable post‐buckling branch and an (initially) stable branch. Results show that perturbations in the fiber path can nudge a structure into a more stable post‐ buckling path by promoting a post‐buckling path using local changes in structural stiffness. The robustness of improved designs can also increase, making structures less susceptible to local fiber misalignments.