The stochastic actor-oriented model is a statistical model for network dynamics, meant to be used for network panel data, that is, repeated measurements of a network on a given set of actors. This chapter gives an introduction to the probability model, in three flavors: a short intuitive explanation, a long conceptual one, and a mathematical explanation. These alternative, complementary formulations cater to readers with different interests, backgrounds, and preferences. The model assumes that between the moments of measurement, the network changes gradually in unobserved small steps. The heart of the model is the ministep, playing a basic role together with the evaluation function and the rate function. The ministep is the fundamental event in which actors have the opportunity of changing one network tie; the subsequently measured networks are connected by a sequence of unobserved ministeps. The probabilities of network change in the ministep depend on the evaluation function according to a conditional multinomial logit model. The rate at which ministeps take place is given by the rate function. The model is also formulated as a simulation model. The chapter ends with a brief history of the model.