Information propagation in robot swarms is critical for coordinated behavior, since collective actions depend on the exchange of messages among robots. However, a predictive model linking the swarm parameters to the dynamics of information propagation has yet to be established. We introduce an epidemiology-inspired approach based on the Susceptible–Infected model to predict information propagation in mobile robot swarms executing random walks. The propagation rate is empirically related to robot density, communication range, and motion speed, yielding a predictive model that accurately reproduces the temporal evolution of the informed fraction across diverse swarm configurations.