Several methods for determining a numerical distance between languages have been proposed in the literature. In this paper we implement one of them, the ALINE distance. We also develop a methodology for comparing its results with other language distance metrics. In particular, we generate trees from distance matrices created by the language distance metrics using two different algorithms developed by computational biologists: Neighbor Joining and UPGMA. We compare these automatically generated trees with expert trees based on those compiled by the Ethnologue project using a tree distance metric also developed by computational biologists. By determining how close the trees generated using the language distance metrics are to the expert trees, we are able to compare different language distance metrics with one another. We compare the ALINE distance with another leading metric, the LDND distance, proposed by the ASJP project. Both metrics perform similarly on the datasets processed, though details differ in sometimes interesting ways.