Automotive stability at the limits of handling requires controllers that keep yaw rate and sideslip within a safe envelope. A time-efficient driver model was built in MATLAB/Simulink using a bicycle model with a nonlinear Pacejka tyre formulation. Phase-plane analysis (yaw rate vs. front tyre slip angle) was used to define the stability boundaries and to evaluate controller behaviour. The vehicle model was first validated against a high-fidelity ADAMS™ simulation to confirm model fidelity; this validation preceded controller design and did not assess controller performance. The primary controller is a Model Predictive Control (MPC) scheme that anticipates system response and modulates longitudinal acceleration to prevent envelope violation, with steering treated as a measured disturbance. For comparison, PID and fuzzy logic controllers were also implemented: PID offers simplicity and fast response, whereas fuzzy logic provides rule-based robustness to nonlinearities but requires tuning. Simulation results show that all three approaches can constrain yaw and slip under varying conditions, while MPC delivers the most consistent envelope enforcement, albeit with higher computational cost, providing faster and more precise intervention suitable for real-time stability control.