Strisores is a clade of neoavian birds that include diurnal aerial specialists such as swifts and hummingbirds, as well as several predominantly nocturnal lineages such as nightjars and potoos. Despite the use of genome-scale molecular datasets, the phylogenetic interrelationships among major strisorean groups remain controversial. Given the availability of next-generation sequence data for Strisores and the clade’s rich fossil record, we reassessed the phylogeny of Strisores by incorporating a large-scale sequence dataset with anatomical data from living and fossil strisoreans within a Bayesian total-evidence framework. Combined analyses of molecular and morphological data resulted in a phylogenetic topology for Strisores that is congruent with the findings of two recent molecular phylogenomic studies, supporting nightjars (Caprimulgidae) as the extant sister group of the remainder of Strisores. This total-evidence framework allowed us to identify morphological synapomorphies for strisorean clades previously recovered using molecular-only datasets. However, a combined analysis of molecular and morphological data highlighted strong signal conflict between sequence and anatomical data in Strisores. Furthermore, simultaneous analysis of molecular and morphological data recovered differing placements for some fossil taxa compared with analyses of morphological data under a molecular scaffold, highlighting the importance of analytical decisions when conducting morphological phylogenetic analyses of taxa with molecular phylogenetic data. We suggest that multiple strisorean lineages have experienced convergent evolution across the skeleton, obfuscating the phylogenetic position of certain fossils, and that many distinctive specializations of strisorean subclades were acquired early in their evolutionary history. Despite this apparent complexity in the evolutionary history of Strisores, our results provide fossil support for aerial foraging as the ancestral ecological strategy of Strisores, as implied by recent phylogenetic topologies derived from molecular data.