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Rent's rule has been successfully applied to a priori estimation of wire length distributions. However, this approach is very restrictive: the circuits are assumed to be homogeneous. In this paper, recursive clustering is described as a more advanced model for the partitioning behavior of digital circuits. It is applied to predict the variance of the terminal count distribution. First, the impact of the block degree distribution is analyzed with a simple model. A more refined model incorporates the effect of stochastic self similarity. Finally, the model is further extended to describe the effects of heterogeneity. This model is a promising candidate for more accurate a priori estimation tools.