Linear programming is an operational research technique widely used to identify and optimize management decision. Its application encourages businesses to increase their output. Instead, however, many organizations most commonly adopt the trial-and-error method. As such, companies find it challenging to distribute scarce resources in a manner that maximizes profit. This study focuses on implementing linear programming to optimize the profit of a manufacturing sector based on the optimized (best possible, efficient) use of raw materials. Our study uses the data gathered on five market bread types from Baker's Cottage reports, i.e., chicken floss, spicy floss, Frank Cheese, Mexico bun, and doughnut. This attribute has been recognized as a linear programming problem mathematically built that was solved using Excel software. The result showed that the Baker’s Cottage unit had to produce 332 loaves of Chicken Floss and 196 loaves of Frank Cheese, as these products objectively contributed to the profit. In contrast, other types of bread did not have to be produced, as their value turned to zero to achieve the maximum monthly profit.