In recent years, airline operators have not only relied on commercial passenger transport but now depended as well on the income generated by air cargo transport. Inspiring a resurgence and forecast of greater market share for aircraft specific to air freight. To achieve competitive and economic operations, air cargo freighters investigate optimizing many processes within the air cargo loading workflow. One such task is the selection and loading of an aircraft with its designated payload as stakeholders are keen on visualizing the scope of this problem and understanding the tradeoffs between economic objectives, commercial objectives, and design constraints. This is described as the Aircraft Weight and Balance problem, which is a deceptively complex problem that presents itself as a generalized assignment problem. This study presents the development of a fuzzy linear programming model as a decision support tool for air cargo operations in the selection and placement of payload for an optimally transported freight. In contrast with previous studies, which had only considered one or two objectives for optimization, the proposed fuzzy linear programming model allows to maximize the payload, maximize the priority of the package, and minimize the operational cost related to the cargo. This approach provides analysis and visual consideration of more practical operations scenarios in finding solutions that conform to business goals and aircraft regulatory and design limitations. A case study is performed to evaluate the effectiveness of the model. A commercial optimizer engine was used and has been shown to provide solutions to the problem within a short time frame.