Supertree methods combine trees on subsets of a taxon set together to produce a tree on the entire set of taxa. SuperFine is a meta-method that utilizes a novel two-step procedure in order to improve the accuracy and scalability of supertree methods. Studies using both simulated and empirical data have shown that SuperFine-boosted supertree methods produce more accurate trees than standard supertree methods, and run more quickly particularly on very large datasets. We present an overview of the SuperFine approach, compare the performance of boosted and unboosted methods on simulated and empirical data, and describe other novel phylogenetic applications that incorporate SuperFine-boosted supertree methods.