This study investigates the variation of cutting force coefficients (CFCs) in milling operations and their impact on force predictions and stability analysis. While CFCs are often assumed constant for simplicity, they are inherently dependent on feed per tooth and cutting speed, introducing uncertainties in machining dynamics. Using an oblique transformation model, CFCs are predicted from an orthogonal cutting database, considering chip thickness and cutting speed. The results indicate that variations in CFCs significantly influence cutting force estimations, affecting stability predictions based on the stability lobe diagram (SLD). Assuming constant CFCs may lead to inaccurate force predictions, miscalculated stability limits, and increased risk of chatter. This can result in excessive forces, accelerated tool wear, poor surface quality, and potential scrap part. In this study, cutting forces are compared against predictions from both constant and variable CFC models, revealing the improved accuracy of the latter in dynamic milling conditions. The influence of cutting speed and feed per tooth on tangential, radial, and axial force components is systematically analysed. It is observed that higher cutting speeds tend to reduce CFC values due to thermal softening effects, whereas increased feed per tooth generally amplifies force coefficients because of increased chip loads. A stability model incorporating CFC variations may provide a more accurate representation of process dynamics. The study emphasises the necessity of adaptive force and stability models in machining simulations to enhance predictive accuracy. These findings offer critical insights for optimising process parameters, selecting stable cutting conditions, and designing chatter avoidance strategies in industrial applications.