In statistics and statistical physics, the Metropolis–Hastings algorithm is a Markov chain Monte Carlo (MCMC) method for obtaining a sequence of random samples from a probability distribution from which direct sampling is difficult.

The algorithm was named after Nicholas Metropolis, who authored the 1953 paper Equation of State Calculations by Fast Computing Machines together with Arianna W. Rosenbluth, Marshall Rosenbluth, Augusta H. Teller and Edward Teller.