Since its introduction, Donath`s technique for predicting placement wire length distributions has become one of the most popular techniques for a priori wire length estimation. However, in its original form, it was heavily constrained by the underlying circuit and architecture models. In this paper, we show how a careful relaxation of those constraints results in very high correlations between predicted and experimentally measured average wire lengths as well as in a much improved accuracy in predicting wire length distributions. Because the availability of the Rent characteristic is crucial for the quality of our model, we investigate how the prediction quality degrades when only an estimated characteristic is available. Such an estimation can be required to save computation time or when the complete netlist is not yet available (partial use of typical values). It turns out that a fitted beta-model, based on only a few partitioning levels, can still result in a relatively high prediction quality. In particular with respect to the wire length distribution, the results are considerably better than when Rent`s rule is used.