This paper presents a novel method for tuning cascade control systems in which both primary and secondary controllers are tuned simultaneously by directly using plant data without resorting to process models. The required plant data are collected from a one-shot step test that can be conducted under either closed-loop or open-loop conditions. The goal of the proposed design is to obtain the parameters of two proportional-integral-derivative (PID) controllers such that the resulting inner and outer loops behave as closely to appropriately specified reference models as possible. The optimization problems related to the proposed design are derived. On the basis of the rationale behind cascade control, the secondary controller is designed to attenuate disturbance faster. The primary controller is designed to accurately account for the inner loop dynamics without requiring an additional test. Moreover, robustness consideration is included in the proposed tuning method, which enables the designer to explicitly address the trade-off between performance and robustness for inner and outer loops independently. Simulations show that the proposed method exhibits superior control performance compared with the existing (model-based) design methods, confirming the effectiveness of this novel method of PID controller design for cascade control systems.