<p>This paper is concerned with optimality conditions and sensitivity analysis for parametric nearly convex minimax programming problems. To this end, we develop formulas for computing the subdifferentials in the nearly convex sense of maximum functions under suitable qualification conditions. Subsequently, we apply these tools to derive the optimality conditions for the problem under consideration. Finally, we establish formulas for calculating the subdifferentials and singular subdifferentials of the optimal value function of the problem in question. Some illustrative examples are provided to demonstrate our findings. The results of this paper not only contribute to a systematic study of minimax programming problems by considering a nontrivial extension of the convex case, but also offer a promising research direction on differential stability in parametric nearly convex multiobjective optimization, due to the close relationship between these two types of optimization problems.</p>