In the present study, an attempt is made to optimize the electrical performance of the thin polymeric films through optimization techniques. The study is conducted in two phases: (1) laboratory experiments and (2) through numerical optimization. For laboratory analysis, thin and transparent films are prepared using polyethersulfone (PES) as host material and meta-nitroaniline (MNA) as guest materials. A set of nine film samples are prepared by the solution casting method in the laboratory using different concentrations of MNA. The electrical properties capacitance, conductance, and dissipation factor of films are measured by Aligent Impedance Analyzer. These characteristics are then optimized mathematically. For this purpose, initially single-objectives are considered for optimizing the electrical properties individually, and later a multiobjective model is considered for analyzing the properties simultaneously. The algorithms employed are metaheuristics: genetic algorithms, particle swarm optimization, differential evolution, and its variant modified differential evolution along with fmincon (a MATLAB toolbox) for single-objective optimization and multiobjective differential evolution algorithm and nondominated sorting genetic algorithm-II for multiobjective optimization.