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This paper presents a method of estimation parameters and acceleration factor of Kumaraswamy-Inverse Weibull Distribution based on constant stress partially accelerated life tests. Depending on progrssive type-II censoring, we present the maximum likelihood, Bayes, and two parametric bootstrap methods. In addition, we use the asymptotic variance covariance matrix of the estimators to construct the approximate confidence intervals, bootstrap and credible confidence intervals. Furthermore, we apply Markov Chain Monte Carlo method to compute the Bayes estimators. Also, generating Markov Chain Monte Carlo samples from the posterior density functions using Gibbs within the Metropolis-Hasting algorithm is studied. Finally, a numerical example is discussed to illustrate different methods of point estimation and confidence intervals.

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