Railway track, as a critical infrastructure, plays a significant role in freight transportation. However, Railway track degrades with age and usage and can impact negatively track availability and safety. Tamping actions are used to rejuvenate the degradation and recover the functionality of the track to an acceptable level. Tamping actions are performed in a form of preventive and corrective regimes. In performing an effective tamping regime, the recovery of both preventive and corrective tamping should be taken into account. In addition, the occurrence of isolated defects should be considered. By combining the recovery model with the degradation model, the long-term behavior of the track geometry can be predicted, and an accurate estimation of tamping needs can be provided, leading to optimum tamping scheduling. In this study, the effects of tamping recovery are modeled for both preventive and corrective strategies. For this aim, the values of both standard deviation (SD) and isolated defects have been predicted and their values before tamping are used as explanatory variables in a multivariable regression model. Finally, the effect of tamping recovery on the values of both SD and isolated defects is estimated. A case study is performed on a heavy haul line located in Sweden’s rail network to evaluate the performance of the proposed multivariable regression model. Observations showed that the model and its coefficients are significant with P-values close to zero, and the R-squared value suggests that the model explains approximately 70% of the variability in the response variable recovery.