Many bacterial pathogens rely on dedicated secretion systems to translocate virulence proteins termed ‘effectors’ into host cells. These effectors engage and manipulate host cellular functions to support bacterial colonization and propagation. The secretion systems are molecular machines that recognize targeting ‘features’ in these effector proteins in vivo to selectively and efficiently secrete them. The joint analysis of whole genome sequencing data and computational predictions of amino acid characteristics of effector proteins has made available extensive lists of candidate effectors for many bacterial pathogens, among which Dot/Icm type IVB secretion system in Legionella pneumophila reigns with the largest number of effectors identified to-date. This system is also used by the causative agent of Q fever, Coxiella burnetii, to secrete a large pool of distinct effectors. By comparing these two pathogens, we provide an understanding of the rationale behind effector repertoire expansion. We will also discuss recent bioinformatic advances facilitating high-throughput discovery of secreted effectors through in silico ‘feature’ recognition, and the current challenge to substantiate the biological relevance and bona fide nature of effectors identified in silico.