There are many cases in which one has continuous flows over networks, and there is interest in predicting and monitoring such flows. This paper provides Bayesian models for two types of networks—those in which flow can be bidirectional, and those in which flow is unidirectional. The former is illustrated by an application to electrical transmission over the power grid, and the latter is examined with data on volumetric water flow in a river system. Both applications yield good predictive accuracy over short time horizons. Predictive accuracy is important in these applications—it improves the efficiency of the energy market and enables flood warnings and water management.