The subject of this chapter is to describe the methodology for assessing the power of phylogenetic HGT detection methods. Detection power is defined in the framework of hypothesis testing. Rates of false positives and false negatives can be estimated by testing HGT detection methods on HGT-free orthologous sets, and on the same sets with in silico simulated HGT events. The whole process can be divided into three steps: obtaining HGT-free orthologous sets, in silico simulation of HGT events in the same set, and submitting both sets for evaluation by any of the tested methods.Phylogenetic methods of HGT detection can be roughly divided into three types: likelihood-based tests of topologies (Kishino-Hasegawa (KH), Shimodaira-Hasegawa (SH), and Approximately Unbiased (AU) tests), tree distance methods (symmetrical difference of Robinson and Foulds (RF), and Subtree Pruning and Regrafting (SPR) distances), and genome spectral approaches (bipartition and quartet decomposition analysis). Restrictions that are inherent to phylogenetic methods of HGT detection in general and the power and precision of each method are discussed and comparative analyses of different approaches are provided, as well as some examples of assessing the power of phylogenetic HGT detection methods from a case study of orthologous sets from gamma-proteobacteria (Poptsova and Gogarten, BMC Evol Biol 7, 45, 2007) and cyanobacteria (Zhaxybayeva et al., Genome Res 16, 1099-108, 2006).