Seismic reflections are physically explained by contrasts in elastic properties in the subsurface, and rock physics is the science that links the seismic properties to geologic properties. Rock physics models attempt to quantify rock properties with physical parameters like clay content, saturation, and porosity, and use this to predict elastic rock properties, and further to extrapolate to scenarios that have not yet been observed. There are rock physics models made for friable sands, cemented sands, shaly sands, sandy shales, uncemented and cemented shales, to mention a few. Sometimes a large selection of available rock physics models can be more confusing than a blessing: Which model is best suited to predict the observations of a given data set, and how do we know that the model we choose is optimally calibrated to the data? This paper proposes a strategy to evaluate numerous rock physics models in a short time. The method finds the best prediction for each model, which makes it easy to see which models are suited for further modeling. The strategy is applied on a data set from the North Sea Brent group. A selection of the rock physics models with the obtained optimal input parameters is further tested to evaluate the ability to predict data outside the calibration data set. The modeling strategy presented ensures a minimum discrepancy between modeled and recorded data, without abandoning rock physics principles.