AbstractLow‐velocity impact experiments are essential for evaluating the mechanical behavior and impact resistance of composite materials in engineering applications. These experiments are primarily based on the measurement of the force‐time signal and a few parameters, including impact energy, impact velocity, and mass. All other parameters, such as displacement, velocity, and absorbed energy, are subsequently derived from these fundamental inputs. This paper first investigates the influence of miscalibration of the force signals, highlighting its significant impact on the reliability of the calculated displacement, velocity, and absorbed energy. Specifically, a miscalibration error of 10% can result in more than 20% error in maximum deflection and over 40% error in absorbed energy. Second, this study introduces a novel force calibration method based on the principle that composite materials absorb negligible energy during low‐energy impacts below the damage threshold. The proposed method is validated using a theoretical mass‐spring model, demonstrating its effectiveness in improving force signal accuracy. Calibration enhances the consistency of maximum force values, reducing deviation by an average of 6.45%, and aligning force‐displacement curves with theoretical predictions. Additionally, the calibration procedure significantly reduces the residual absorbed energy from an initial range of 1.084–1.226 J to a negligible 0.013–0.030 J, yielding values that are more reliable for tests conducted at impact energies below the damage threshold. Hence, this study highlights the importance of proper calibration in improving the reliability of impact experiments and provides a robust framework for achieving accurate and consistent results.Highlights A new force calibration method for low‐velocity impact tests is proposed. Incorrect calibration significantly affects the accuracy of impact energy and displacement. The method ensures accurate energy absorption estimates for polymer composites. It is validated using a mass‐spring model, improving force signal reliability. The approach improves the repeatability and accuracy of impact experiments.