The plant immune signaling network needs to be robust against attack from fast-evolving pathogens and tunable to optimize immune responses. We investigated the basis of robustness and tunability in the signaling network controlling pattern-triggered immunity (PTI) in Arabidopsis. A dynamic network model containing four major signaling sectors, the jasmonate, ethylene, phytoalexin-deficient 4, and salicylate sectors, which together govern up to 80% of the PTI levels, was built using data for dynamic sector activities and PTI levels under exhaustive combinatorial sector perturbations. Our regularized multiple regression model had a high level of predictive power and captured known and unexpected signal flows in the network. The sole inhibitory sector in the model, the ethylene sector, contributed centrally to network robustness via its inhibition of the jasmonate sector. The model's multiple input sites linked specific signal input patterns varying in strength and timing to different network response patterns, indicating a mechanism enabling tunability.