Crash testing plays a crucial role in ensuring the safety and reliability of automotive vehicles. Traditional crash test methods rely heavily on physical experiments, which can be time-consuming, expensive, and often limited in their ability to provide detailed information about the dynamic behavior of a vehicle during a crash. In recent years, there has been a growing interest in the development of simulation models that can accurately predict the behavior of vehicles during a crash, thereby reducing the need for extensive physical testing. This research aims to enhance crash testing methodologies by incorporating sensor-embedded bumpers into the simulation process, with a focus on utilizing the LS-DYNA software package. The integration of advanced sensor technology into the bumper design allows for the collection of real-time data during a crash, enabling more accurate and reliable simulation models. The first phase of the research involves the development of a sensor-embedded bumper prototype capable of measuring key parameters such as impact force, acceleration, and deformation. The bumper design incorporates high-precision sensors strategically placed to capture critical data points during a crash event. These sensors are carefully calibrated and synchronized with the LS-DYNA simulation environment to ensure accurate representation of the crash dynamics. The second phase focuses on the implementation of the sensorembedded bumpers within the LS-DYNA simulation framework. Advanced algorithms are employed to seamlessly integrate the real-time sensor data into the simulation models, enhancing the accuracy and reliability of the crash simulations. Furthermore, the collected data from the sensor-embedded bumpers are utilized to validate and calibrate the simulation models, thereby improving their predictive capabilities. To evaluate the effectiveness of the enhanced crash testing methodology, a comprehensive series of simulations and physical crash tests are conducted. A range of crash scenarios, including frontal, side, and rear impacts, are considered to assess the performance and reliability of the sensor-embedded bumper approach. The results are compared with traditional crash testing methods, and the advantages and limitations of the proposed methodology are discussed. The outcomes of this research are expected to contribute to the development of more reliable simulation models for crash testing. The integration of sensor-embedded bumpers enhances the accuracy of crash simulations, enabling automotive manufacturers to optimize vehicle safety designs and reduce the need for extensive physical testing. Ultimately, this research aims to improve overall vehicle safety and support the ongoing efforts to enhance occupant protection in automotive crashes.