In his recently-published critiques, Reeves provides numerous important suggestions for the improvement of baraminology as well as pointed criticism of baraminic distance correlation (BDC). Given that BDC violates certain methodological assumptions, Reeves concludes that it is at best a heuristic of unknowable utility. Here, I evaluate 82 distance matrices taken from a previous study of Cenozoic mammals. After defining a BDC clustering method, I find that Pearson-based BDC performs as well as or better than medoid partitioning, fuzzy clustering, and Spearman-based BDC. The majority of Pearson BDC clusters (68.9%) also appear as clades in published phylogenies using the same character sets. I therefore conclude that despite questions about its formal validity, Pearson BDC remains a useful heuristic for clustering taxa and should not be rejected merely on the basis of Reeves's critique. Because a large minority of studies revealed disagreement between different clustering methods, greater uncertainty about the previous baraminological conclusions was introduced using medoid partitioning and fuzzy clustering. Consequently, I recommend using multiple clustering techniques (Pearson BDC, Spearman BDC, fuzzy analysis, and medoid partitioning) in future baraminology studies.