We describe a computational platform to predict atherosclerotic plaque onset and growth in carotids. It integrates in-vivo data, Computational Fluid Dynamics (CFD) simulations and a model for plaque growth linearly correlating the plaque progression with low values of time-averaged Wall Shear Stresses (WSS). We show that steady CFD simulations give the same averaged-WSS values as unsteady simulations. Therefore, the model for plaque growth can be coupled with steady simulations, reducing the computational costs. Finally, by comparing the numerical predictions with the in-vivo data, we show that a modification must be introduced in the plaque growth model to obtain acceptable results.