The asymptotic probability distribution of identified black-box transfer function models is studied. The main contribution is that we derive variance expressions for the real and imaginary parts of the identified models that are asymptotic in both the number of measurements and the model order. These expressions are considerably simpler than the corresponding ones that hold for fixed model orders, and yet they frequently approximate the true covariance well already with quite modest model orders. We illustrate the relevance of the asymptotic expressions by using them to compute uncertainty regions for the frequency response of an identified model