In structural engineering, modeling fulfills a key role to simulate the behavior of structures, but even very detailed models may fail to represent critical mechanisms. The uniqueness and uncertainties associated with civil structures make the prediction of the actual mechanical characteristics and the structural performance, a difficult task. Reliable estimates require calibration of system parameters based on measured experimental response data. To date, several different approaches have been adopted in literature. Generally, these ones try to minimize the difference between the model output and the experimental data. However, inverse problems (such as the estimate of mechanical parameters) when treated deterministically, are typically ill-conditioned and often ill-posed, since the values of parameters used to predict the structural behavior are uncertain owing to simplifying and approximate assumptions on model.