This paper introduces a fast, easy and accurate Gibbs sampling algorithm to develop a Bayesian inference for a multiplicative seasonal autoregressive moving average (SARMA) model. The proposed algorithm generates from normal and inverse gamma distributions and does not involve any Metropolis-Hastings generation. Simulated examples and a real data set are used to illustrate the proposed algorithm.