In an economy characterized by inflation, instability, and constant shifts, the travel industry that the case company operates has experienced significant volatility in unit costs. Furthermore the company has seen growth in unit volume exacerbating the problem. These recent developments have deemed the old pricing method outdated. An accurate pricing method would alleviate many of the these issues and promote sustainable growth. This master thesis project report presents the development and analysis of a capacity based price model, which is intended to enhance the pricing strategy of a specific product line. The pricing model was created in Python with data provided by the company. The model's output was supposed to give the company an adjustment to their standard budget price. During the project, discoveries about the data were made as there was varying qualities. The report thoroughly explores a comprehensive discussion regarding the linkages of risk factors, encompassing the impact of this developed model on the company's overall risk management, including market, and operational risks. A Monte Carlo based model risk analysis is conducted to get a quantitative risk metric.