The challenges of steering-by-wire (SBW) systems in vehicles are due to the absence of a direct mechanical link between the steering wheel and the wheels on the road. This limitation imposes the necessity of employing sophisticated control systems to attain the highest accuracy and stability during operation. In such systems, the responsibility rests completely on the utilised controller to change the wheel’s angle on the road swiftly and accurately in response to the steering wheel changes by the driver. However, conventional control systems suffer slowly in responding to instructions and some fixed errors in their steady-state phase. The current study introduces an innovation of a model that integrates model predictive control (MPC) with particle swarm optimisation (PSO) to improve the performance of SBW systems. The MPC procedure is typically employed to control system responses over a timeframe and eliminate unnecessary and ineffective actions according to the specified objectives. The PSO algorithm is used to manage the ineffective parameters within the MPC. Results revealed that the proposed approach remarkably and effectively shortens response time, enhances wagon stability and reduces the settling error to nearly null. In addition, the integration of PSO with the overall system performance enhances the tuning of the response time, hence augmenting the system efficiency and responsiveness. The study outcomes support the proposal that the control strategy can improve the efficiency of SBW systems with high operational goals.