Probability statements in applied science cannot be verified, i.e., shown to be true. But, as shown, the models or methods that generate probability statements can be validated in the sense that they can be assessed using real or simulated data. The performance of probabilistic models can be compared in terms of likelihood, Shannon information or entropy. Likelihood and information provide equivalent measures of relative validity. Examples drawn from weather forecasting and seismic engineering illustrate the approach.