Protein secretion systems are complex molecular machineries that translocate proteins through the outer membrane and sometimes through multiple other barriers. They have evolved by co-option of components from other envelope-associated cellular machineries, making them sometimes difficult to identify and discriminate. Here, we describe how to identify protein secretion systems in bacterial genomes using the MacSyFinder program. This flexible computational tool uses the knowledge gathered from experimental studies to identify homologous systems in genome data. It can be used with a set of predefined MacSyFinder models, “TXSScan,” to identify all major secretion systems of diderm bacteria (i.e., with inner and LPS-containing outer membranes) as well as evolutionarily related cell appendages (pili and flagella). For this, it identifies and clusters co-localized genes encoding proteins of secretion systems using sequence similarity search with Hidden Markov Model (HMM) protein profiles. Finally, it checks if the clusters’ genetic content and genomic organization satisfy the constraints of the model. TXSScan models can be altered in the command line or customized to search for variants of known secretion systems. Models can also be built from scratch to identify novel systems. In this chapter, we describe a complete pipeline of analysis, starting from (i) the integration of information from a reference set of experimentally studied systems, (ii) the identification of conserved proteins and the construction of their HMM protein profiles, (iii) the definition and optimization of “macsy-models,” and (iv) their use and online distribution as tools to search genomic data for secretion systems of interest. MacSyFinder is available here: https://github.com/gem-pasteur/macsyfinder, and MacSyFinder models here: https://github.com/macsy-models.