This paper discussed the problem of estimating of the stress-strength reliability R =
P r(Y < X). It is assumed that the strength of a system X, and the environmental stress applied
on it Y, follow the Quasi Lindley Distribution(QLD). Stress-strength reliability is studied using
the maximum likelihood, and Bayes estimations. Asymptotic confidence interval for reliability is
obtained. Bayesian estimations were proposed using two different methods: Importance Sampling
technique, and MCMC technique via Metropolis-Hastings algorithm, under symmetric loss
function (squared error) and asymmetric loss functions (linex, general entropy). The behaviors
of the maximum likelihood and Bayes estimators of stress-strength reliability have been studied
through the Monte Carlo simulation study.