Abstract: Susceptible (S), Exposed (E), Infectious (I), Quarantine (Q), Recovered (R), Stochastic Compartmental Model for computer virus has been developed and researchers assume that the transmission of virus in computer network are probabilistic. To implement this concept, Reversible Jump Monte Carlo Markovian Chain (MCMC) algorithm has been implemented. The MCMC algorithm basically includes Bayesian inferences, likelihood function, prior distribution, posterior distribution and predictive distribution. The threshold R₀ has been defined to determine the removal of the disease if threshold parameter is at most one, otherwise endemic state exists. The effect of quarantine has been implemented on SEIR Stochastic Model and time dependency has been analyzed by implementing predictive distribution for virus removal time.