NC machining data, which cause excessive cutting force, accelerate tool wear, reduce the roughness of machined surfaces, and in severe cases, result in tool breakage and material waste. Thus, the cutting conditions should be optimized according to the material-spindle speed-feed rate combination. However, it is very difficult to perfectly predict and optimize the dynamic characteristics of machining, such as tool vibration and wear, and spindle thermal deformation. Further, predicted tool paths are accompanied by machining errors. This study proposes an advanced adaptive control method that can balance the machining load, improve tool life, and reduce machining time. The proposed method 1) synchronizes the spindle load and NC-data and stores it, 2) analyzes the stored data to create a reference curve that can balance the machining load, 3) adjusts the tool feed rate using a reference curve, 4) engages rapid traverse when the load is small, and 5) applies an approach feed rate when the tool approaches a workpiece, reducing the impact on the tool when the tool meets the workpiece. Case examples proved that the use of the proposed balanced load reduced machining time and increased tool life.