Nonlinear pricing is widely used in practice and has been proposed as a particularly useful pricing strategy for service products. However, little is known about how to specifically set nonlinear prices for services to maximize profits. Moreover, prior research has primarily discussed the usefulness of nonlinear pricing using mathematical models, while methods for deriving nonlinear pricing structures through simulation models have not been known. Therefore, this study developed a nonlinear pricing simulation model as a step-by-step analytical framework, and discussed the specific application methods and procedures for deriving a near-optimal nonlinear pricing structure (heuristic price path) that maximizes profits for services using this technique. The methodology constituting the simulation model consists of conjoint analysis, regression analysis, and a nonlinear price derivation program developed in this study. The program is a method that finds the prices and quantities that maximize profits through the iterative application of different pricing structures. Therefore, unlike mathematical models, the nonlinear pricing structure derived by this model represents a near-optimal price obtained through a heuristic technique. Additionally, through empirical analysis, we examined whether the profits under nonlinear pricing derived from the simulation model are higher than those under uniform pricing, and which pricing structure among different nonlinear pricing structures generates higher profits. The empirical results demonstrated, consistent with previous research, that nonlinear pricing is a pricing strategy capable of generating more profits than uniform pricing. Furthermore, among nonlinear pricing techniques, profits ranked in the following order from highest to lowest: n-part tariff > two-step tariff > two-part tariff > all-units quantity discount. The pricing method yielding the highest profit among nonlinear pricing was the three-part tariff, which increased profits by 21% compared to uniform pricing.