NONE 20260610054040171 wseas/wseas content-registration-form+ja@crossref.org content-registration-form EQUATIONS 2944-9146 2732-9976 M. Maswadah Department of Mathematics Faculty of Science Aswan University Aswan, EGYPT Abdullah Ali H. Ahmadini Department of Mathematics College of Science Jazan University Jazan, SAUDI ARABIA It is widely recognized that conditional inference is often as efficient as Bayesian inference based on a non-informative prior. However, it is generally less efficient than Bayesian inference that incorporates an informative prior distribution. Accordingly, the primary objective of this study is to derive conditional point estimates for the parameters of the Gumbel distribution using pivotal quantities, based on generalized progressively hybrid-censored data. These estimates are compared with Bayesian estimates obtained under various loss functions through Monte Carlo simulations. 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