Infections with many Gram-negative pathogens, including Escherichia coli, Salmonella, Shigella, and Yersinia, rely on type III secretion system (T3SS) effectors. We hypothesized that while hijacking processes within mammalian cells, the effectors operate as a robust network that can tolerate substantial contractions. This was tested in vivo using the mouse pathogen Citrobacter rodentium (encoding 31 effectors). Sequential gene deletions showed that effector essentiality for infection was context dependent and that the network could tolerate 60% contraction while maintaining pathogenicity. Despite inducing very different colonic cytokine profiles (e.g., interleukin-22, interleukin-17, interferon-g, or granulocyte-macrophage colony-stimulating factor), different networks induced protective immunity. Using data from >100 distinct mutant combinations, we built and trained a machine learning model able to predict colonization outcomes, which were confirmed experimentally. Furthermore, reproducing the human-restricted enteropathogenic E. coli effector repertoire in C. rodentium was not sufficient for efficient colonization, which implicates effector networks in host adaptation. These results unveil the extreme robustness of both T3SS effector networks and host responses.