<p>In multi-axis CNC machining, the performance of feedrate scheduling plays a critical role in determining machining efficiency, accuracy, and surface quality. However, due to the nonlinear relationship between the high-order motion of the tool in the workpiece coordinate system and that of the machine axes, it remains a challenge to generate time-optimal feedrate profiles under velocity, acceleration, and jerk constraints in both the tangential direction and on each axis. To address this issue, this paper proposes a novel jerk-constrained feedrate scheduling method based on constraint-guided sampling, which incrementally grows a tree of feasible nodes through sampling to obtain a time-optimal feedrate profile, unlike existing approaches based on dynamic look-ahead or optimization. To accelerate the tree expansion, constraint-guided sampling and neighbor search strategies are employed to reduce the sampling and search domains. In addition, lazy constraint checking and redundant point avoidance are incorporated to improve computational efficiency. Comparative results demonstrate that the proposed method achieves favorable performance in terms of both machining time and computation time.</p>