The simplex approach for solving linear programming models and its application to business decision-making are the subjects of this article, which was written as a part of the course Quantitative Methods for Business Decision-Making. The subject matter of the study includes mathematical formulations, operations research, linear programming theory, history, and essential components. Economics and mathematics are combined in linear programming, and one of the most applicable models of linear programming is shown by the simplex approach. The thesis presents a real-world example of a manufacturing program with the objective of minimizing costs. By specifying the resources required for production and the working hours, the practical example maximizes the production of Type A and Type B remote controllers. The practical case was solved using the Excel Solver function. The Solver is a tool that discovers the best solution quickly and simply. Configuring the variables, the objective function and the program limitations is essential. The remote control manufacturing program's resource optimization and savings measures are presented in the example. The practical problem was solved in a way that produced both integer and non-integer solutions. The integer answer has been chosen in order to make the solution simpler and more realistic. Multiple businesses may integrate this approach into regular business operations and procedures via quantitative methods and this practical example. This method is very useful for reducing expenses, profitmaximizing, and resource optimization. The scientific and professional literature acts as a foundation for this thesis.