Abstract: Objectives Due to the limited placement of measurement points in the machinery space, the longitudinal vibration of the propulsion shaft system can only be measured at limited locations, making it difficult to comprehensively assess the longitudinal vibration status of the entire shaft system. This study aims to propose a new method that can accurately predict the longitudinal vibration displacement of the entire propulsion shaft system based on a limited number of measurement points. Methods Innovatively integrating Kalman filtering technology with the longitudinal vibration model of the propulsion shafting, a new prediction method for the longitudinal vibration displacement of the shafting is developed. This method is a time-domain prediction approach that combines deterministic analysis with stochastic considerations, fully accounting for the impacts of dynamic model errors and data measurement errors. By implementing a minimum variance unbiased estimation strategy, it effectively enhances the accuracy of displacement prediction. Especially in complex scenarios where the propeller excitation force is unknown and the measurement signals are significantly contaminated by noise, this method can accurately predict the longitudinal vibration displacement at any position of the propulsion shafting based on data input from only two measurement points. Results Even in harsh environments with a signal-to-noise ratio as low as 10 dB, the method maintains high accuracy. The root mean square error (RMSE) between the predicted displacement at the propeller and the theoretical displacement is only 3.35μm, and the RMSE at the thrust bearing is only 1.74 μm. These results fully demonstrate the high-precision prediction capability of this method in low signal-to-noise ratio environments. Conclusions The method proposed in this paper provides a new solution for real-time, online assessment of the longitudinal vibration state of ship propulsion shafting, possessing significant application value.