A necessary and sufficient condition such that there exists a proper stable rational transfer function whose H_∞ norm is less than or equal to a specified value is derived as a matrix inequality composed of its input-output covariances. Then, it is applied to a model invalidation problem with additive bounded uncertainty. A numerical example demonstrates that the model invalidation condition based on input-output covariances is robust against additive measurement noise.