The use of elastomers in modern road vehicles can solve many design conflicts in the development process. The prerequisite for this is a detailed calculability of the component properties, which are dependent on the geometric shape, the choice of material and the parameters of the manufacturing process. A robust method for calculating parameter-property relationships of elastomer bushings based on physical models and machine learning approaches allows these relationships to be calculated in the early phases of vehicle development. Viscoelastic material properties represent a major challenge for the durability design of elastomer components in load data acquisition. With the help of the modeling approaches developed here for load data analysis, load paths with elastomer bushings in the vehicle can be calculated much more accurately for high loads. A new method for experimental component validation is presented, which reduces the costly testing time for operational load tests by up to 85%. This method uses multi-axis block programs and achieves damage patterns comparable to the operational load test.