Investment decisions in onshore wind turbine projects must consider both initial capital expenditures and long-term maintenance costs. Despite the significant research in the renewable energy sector, maintenance costs often do not receive the attention they deserve in feasibility studies and financial planning. This can lead to underestimation of operational expenses, impacting the overall profitability and efficiency of wind farms. This study highlights the necessity of incorporating maintenance cost analysis when selecting locations for wind farm installations. It examines the influence of the main environmental and operational factors on maintenance expenditures, emphasizing their role in long-term asset management. Moreover, the importance of evaluating existing maintenance plans in operational wind farms is discussed, as optimizing these strategies can lead to significant cost reductions and improved turbine lifespan. A neural network model is proposed to predict maintenance costs based on site-specific variables, providing a data-driven approach to enhance decision-making in wind energy investments. By integrating maintenance cost considerations into project planning, stakeholders can achieve more accurate financial forecasts and ensure the sustainability of wind energy infrastructure.