Abstract: In the design of open-pit coal mines in China, the primary task is to define the rational mining boundary, which essentially involves controlling the stripping ratio within the boundary to ensure that it does not exceed the economically reasonable stripping ratio. Traditional methods for calculating the economically reasonable stripping ratio (such as the cost method and comparative method) typically assume that economic parameters like coal prices and stripping costs are fixed values, resulting in a constant economic stripping ratio over a long period. However, coal prices, costs, resource conditions, and mining methods all exhibit strong dynamic characteristics and inevitably change over time. As a result, existing calculation methods cannot effectively address these dynamic changes and fail to provide a dynamic prediction of the economically reasonable stripping ratio, thus impacting the overall economic efficiency of the mine. Based on dynamic economic theory, a calculation method for economically rational stripping ratio is proposed. By improving the safety costs, ecological costs, and the impact of severe climatic conditions. Historical data on pithead prices and long-term contract prices of coal are collected to identify the key factors influencing coal prices. A time-series prediction method based on the VMD - SVR hybrid model is proposed to effectively forecast the future trend of coal prices. Furthermore, the cost structures of different mining techniques are analyzed, and cost calculation models are developed for two typical mining methods: the dragline-truck intermittent method and the dragline-truck-semi-fixed crusher station semi-continuous method. Based on these analyses, a dynamic prediction method for the economically reasonable stripping ratio is proposed, which can effectively address fluctuations in coal prices and changes in mining costs. Using the example of the Zhundong open-pit coal mine, the results show that the economically reasonable stripping ratio for the mine will increase from 10.0 m³/t to 16.4 m³/t over the next five years. This provides a basis for the rational delineation of the mining boundary. The dynamic prediction method for the economically rational stripping ratio, based on dynamic economic theory, can provide practical and effective data support for the rational delineation of mining boundaries.