This study presents an analytical model for estimating cutting forces in excavator-mounted drum cutters, with particular emphasis on the importance of experimental results in validating and refining theoretical models under varying operational conditions. The model integrates theoretical formulations with empirical data obtained from experiments in which operational parameters, including cutting speed, feed rate, and pressure, were varied while maintaining a constant cutting environment. These variations in operational conditions were crucial for calibrating the model and evaluating its accuracy. The validation of the model against experimental results demonstrated a high degree of precision in predicting cutting forces. This approach underscores the importance of adjusting operational conditions to refine theoretical models, thereby significantly enhancing predictive accuracy. The insights gained from this validation process enable better optimization of drum cutter performance, leading to improved operational efficiency, reduced wear, and lower costs. The study demonstrates the crucial role of experimental testing in enhancing the reliability of predictive models for excavator-mounted drum cutters.