  We study a probabilistic variant of binary session types that relate to a
class of Finite-State Markov Chains. The probability annotations in session
types enable the reasoning on the probability that a session terminates
successfully, for some user-definable notion of successful termination. We
develop a type system for a simple session calculus featuring probabilistic
choices and show that the success probability of well-typed processes agrees
with that of the sessions they use. To this aim, the type system needs to track
the propagation of probabilistic choices across different sessions.
