<p>Stability lobe diagrams (SLDs) are widely used to select spindle speed and depth of cut in turning and milling operations; however, they distinguish only between stable and unstable cutting and do not characterize the dynamic behavior within the stable region. Nominally stable conditions may still exhibit high vibration sensitivity and long transient responses, which can degrade surface quality and reduce process reliability. This work proposes a robustness-based extension of classical SLDs for quantitative characterization of stable cutting dynamics. Unlike existing robustness-oriented approaches, the proposed framework does not require explicit uncertainty modeling and relies solely on nominal system dynamics. To ensure practical relevance, the framework is demonstrated using well-established benchmark parameters for turning and experimentally-obtained modal data for a milling benchmark system. This approach relies on standard modal data without requiring additional cutting trials or explicit uncertainty modeling, making it directly applicable in industrial environments. The methodology integrates pole-based analysis, transient metrics, and frequency-domain stability margins to identify dynamically fragile regions. Additionally, a conservative inner stability limit is derived using the small-gain theorem, providing a sufficient chatter-free boundary that guarantees stability under worst-case loop amplification. By balancing productivity with vibration resilience, these robustness maps serve as a predictive decision-support tool to improve process consistency and reliability on the shop floor by eliminating the reliance on trial-and-error and avoiding sensitive operating zones.</p>