In a previous study by Sarkar et al. (Metall. Mater. Trans. B 46B:961 2015), a dynamic model of the LD steelmaking was developed. The prediction of the previous model (Sarkar et al. in Metall. Mater. Trans. B 46B:961 2015) for the bath (metal) composition matched well with the plant data (Cicutti et al. in Proceedings of 6th International Conference on Molten Slags, Fluxes and Salts, Stockholm City, 2000). However, with respect to the slag composition, the prediction was not satisfactory. The current study aims to improve upon the previous model Sarkar et al. (Metall. Mater. Trans. B 46B:961 2015) by incorporating a lime dissolution submodel into the earlier one. From the industrial point of view, the understanding of the lime dissolution kinetics is important to meet the ever-increasing demand of producing low-P steel at a low basicity. In the current study, three-step kinetics for the lime dissolution is hypothesized on the assumption that a solid layer of 2CaOAESiO 2 should form around the unreacted core of the lime. From the available experimental data, it seems improbable that the observed kinetics should be controlled singly by any one kinetic step. Accordingly, a general, mixed control model has been proposed to calculate the dissolution rate of the lime under varying slag compositions and temperatures. First, the rate equation for each of the three rate-controlling steps has been derived, for three different lime geometries. Next, the rate equation for the mixed control kinetics has been derived and solved to find the dissolution rate. The model predictions have been validated by means of the experimental data available in the literature. In addition, the effects of the process conditions on the dissolution rate have been studied, and compared with the experimental results wherever possible. Incorporation of this submodel into the earlier global model (Sarkar et al. in Metall. Mater. Trans. B 46B:961 2015) enables the prediction of the lime dissolution rate in the dynamic system of LD steelmaking. In addition, with the inclusion of this submodel, significant improvement in the prediction of the slag composition during the main blow period has been observed.