This article describes the experimental calibration of a three-dimensional numerical model of an Alfa Pendular train vehicle based on modal parameters. The dynamic tests of the carbody and bogie of the vehicle allowed the determination of the frequencies and modal configurations of 13 vibration modes, by applying the data-driven stochastic subspace identification method. In addition, a dynamic characterisation test of the passenger-seat system was also conducted. The calibration of the model was performed using a submodelling/multistep approach involving two phases, the first one focused on the calibration of the model of the bogie under test conditions and the second one focused on the calibration of the complete model of the vehicle. The calibration was performed through an iterative method based on a genetic algorithm and allowed to obtain optimal values of 17 parameters of the numerical model. For the pairing of the vibration modes, real and complex, a recent technique was used based on the calculation of the modal strain energy. The stability of a significant number of parameters considering different initial populations demonstrated the robustness of the algorithm. The comparison of experimental and numerical responses before and after calibration revealed significant improvements in the numerical model and a very good correlation between the responses obtained with the calibrated model and the experimental responses.