This paper reviews and analyzes the applications of maintenance optimization models. It discusses the role of these models in maintenance management and the factors that have hindered their application. The paper also explores future prospects for these models. Maintenance optimization models are mathematical models that quantify the costs and benefits of maintenance and aim to achieve an optimal balance between them. These models have been developed since the 1960s by researchers such as Barlow, Proschan, Jorgenson, McCall, Radner, and Hunter. They include models such as age and block replacement models. The paper reviews the applications of these models and discusses the challenges in their implementation. It also highlights the importance of data collection and analysis in applying these models. The paper notes that while maintenance optimization models have been applied in various industries, there are still challenges in their widespread adoption. These include the need for decision support systems, the difficulty in quantifying maintenance benefits, and the gap between theory and practice. The paper also discusses the role of software packages in implementing maintenance optimization models and the importance of data in these models. Finally, the paper concludes that maintenance optimization models have the potential to improve maintenance management and that future developments in technology and economic necessity will likely increase their application.This paper reviews and analyzes the applications of maintenance optimization models. It discusses the role of these models in maintenance management and the factors that have hindered their application. The paper also explores future prospects for these models. Maintenance optimization models are mathematical models that quantify the costs and benefits of maintenance and aim to achieve an optimal balance between them. These models have been developed since the 1960s by researchers such as Barlow, Proschan, Jorgenson, McCall, Radner, and Hunter. They include models such as age and block replacement models. The paper reviews the applications of these models and discusses the challenges in their implementation. It also highlights the importance of data collection and analysis in applying these models. The paper notes that while maintenance optimization models have been applied in various industries, there are still challenges in their widespread adoption. These include the need for decision support systems, the difficulty in quantifying maintenance benefits, and the gap between theory and practice. The paper also discusses the role of software packages in implementing maintenance optimization models and the importance of data in these models. Finally, the paper concludes that maintenance optimization models have the potential to improve maintenance management and that future developments in technology and economic necessity will likely increase their application.