The paper presents development and validation of coal mill model (including the action of classifier) to be used for improved coal mill control. The model is developed by using the mass and heat balance equations of the coal mill. Genetic Algorithm is used to estimate the unknown parameters that are used in the model validation. The advantage is that the raw data used in modeling can be obtained without any extensive mill tests. The simulation results show a satisfactory agreement between the model response and measured value. Apart from the conventional PID controller, inorder to ensure tight control with less overshoot and to handle constraints Model Predictive Controller is designed to maintain outlet temperature and pulverized coal flow at desired set point value.