In the classical Bayesian persuasion model, an informed player and an uninformed one engage in a static interaction. This work extends this classical model to a dynamic setting where the state of nature evolves according to a Markovian law, allowing for a more realistic representation of real‐world situations where the state of nature evolves over time. In this repeated persuasion model, an optimal disclosure strategy of the sender must balance between obtaining a high‐stage payoff and disclosing information that may have negative implications on future payoffs. We discuss optimal strategies under different discount factors and characterize when the asymptotic value achieves the maximal possible value.