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In this work, an inverse problem approach is employed to estimate the suspension parameters of a light vehicle based on field tests. The modeling process of a rear-wheel drive (RWD) vehicle is depicted. The model considers only the vertical dynamics of the vehicle. The experimental data were measured by sensors installed on the vehicle during specific road tests in a proving ground. The inverse problem is solved by using the Particle Swarm Optimization (PSO), minimizing the quadratic error between experimental data and numerical results of the vehicle simulation. Accuracy, computational time, efficiency and efficacy of the model were compared regarding the behavior of the performance responses of the vehicle measured on the road tests. Throughout this process, the vehicle model was validated to be used in future studies of vehicle dynamics.