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One of the alternative distributions used in data analysis when the data not symmetric is the Inverse Weibull Distribution. Inverse Weibul Distribution is obtained from the Weibull Distribution with the transformation variables. Marshall and Olkin (1997) introduced an interesting method of adding a parameter to a well established distribution so we extend the Invers Weibull Distribution by  the Marshall-Olkin method (MOEIW). The probability density function (pdf), cumulative distribution function (cdf), hazard rate, survival function, mode,and quantiles of MOEIW are derived. We also discuss the estimation of the model parameters by maximum likelihood. Expressions for the moments are obtained. We provide an application to real data then compare the model with Gamma Distribution, Weibull Distribution and Inverse Weibull Distribution to see its flexibility. Model comparison using the log likelihood, AIC, and BIC showed that MOEIW fit the data better than the other distributions

Marshall-Olkin, Inverse Weibull Distribution, Maximum Likelihood Estimation, Extended Distribution