The pioneering work of Harry Markowitz in the 1950s introduced the mean-variance portfolio optimization model, a pivotal tool for investors to guide asset selection, allocation, and portfolio weightings. Markowitz's seminal paper, "Portfolio Selection" (1952), underscored the significance of portfolio diversification. Nevertheless, subsequent research has illuminated the model's weaknesses and limitations, drawing substantial attention from scholars such as Fuerst, Norton, Ceria, Stubbs, Goldfarb, Iyengar, Jorion, Konno, Suzuki, Michaud, Bowen, Ravipti, and others. This study delves into the evolution of the Markowitz mean-variance model, propelled by its identified limitations and weaknesses. Researchers including Jobson, Korkie, Ratti, Frost, Savarino, Polson, Tew, Britten-Jones, Kandel, Stambaugh, Zellner, Chetty, Klein, Bawa, Brown, Huang, and Markowitz have explored avenues to enhance the model. Bayesian approaches, predictive probabilities, and Mean-semi variance modifications have been among the strategies employed to refine and extend the Markowitz framework. Furthermore, a distinct thread of research has integrated Random Matrix Theory (RMT) into financial markets, leveraging concepts initially introduced by Wigner (1951). Galluccio, Laloux, Bongini, Pafka, Kondor, Potters, Lindberg, and others have harnessed RMT to augment Markowitz's portfolio optimization, opening new avenues for improving its performance and robustness