Automotive crash simulation is a topic characterized by a high level of complexity. It deals with nonlinear dynamics, sophisticated models of materials and geometry, models of human occupants, as well as a nearly unmanageable of possible boundary and initial conditions. In this complex field, uncertainty management plays an essential role. The lack of information to adequately determine the pertinence of the model assumptions, the inevitable geometrical and material differences between nominally identical cars and the huge number of possible boundary and initial conditions give rise to uncertainties of different origin. These uncertainties are reflected in model parameters of uncertain value, which have to be handled efficiently to obtain a validation of the overall crash simulation. A very practical approach to the modeling and simulation of uncertain systems is the numerical implementation of the uncertain parameters as fuzzy numbers, a special class of fuzzy sets, and then, the use of fuzzy arithmetic based on the transformation method. A fuzzy arithmetical approach for the modeling, simulation and analysis of systems with uncertain parameters has been presented. In this concept, the uncertain parameters are modeled by fuzzy numbers, and the fuzzy-parameterized models are evaluated by the use of the Transformation Method in conjunction with commercial finite element software. In addition to the provision of a worst-case scenario, fuzzy arithmetic based on the Transformation Method allows the quantification of the individual influence of each uncertain model parameter on the overall uncertainty of the system output. On this basis, revealing conclusions can be drawn with respect to the necessity of design modifications or to the importance of preliminary identification or optimization procedures for specific model parameters. Furthermore, against the background that in crash analysis, uncertainties usually exhibit rather drastic effects on the predicted behavior of the structure, it is strongly recommended in future to redirect the increasing computer power to the inclusion of uncertainties, rather than to progress with a further refinement of the finite element models, providing a fake exactness that is not resonable in most cases.