Abstract: We consider Markov Decision Processes where the decision-maker does not observe the state (blind MDPs), and study the computability of the value of the long-duration problem. We prove that, under some ergodic assumptions on the transition, the approximation of the long-duration value is a decidable problem. We also consider the extension of such a result to stochastic games.