The mechanistic modeling of mineral crystallization is essential for the understanding and control of many natural and industrial processes. In the past century, many mechanisms and models have been proposed to explain observations in different crystallization stages. However, most models only focus on a certain step or mechanism (e.g., nucleation, aggregation) and lack a comprehensive view. Incorporating nucleation, aggregation, and surface reaction together, this study developed an analytical two-stage crystallization model to simulate the particle size and number concentration versus time and correlate them with the measured solution turbidity. Through measuring solution turbidity in real time, this model can reproduce the crystallization process by predicting the key parameters: nucleation rate, particle size, number concentration, surface tension, induction time, and particle linear growth rate. Most of these values for barite crystallization match with literature data and our direct cryo-transmission electron microscopy (cryo-TEM) measurements. Moreover, the established relationships of these key parameters versus temperature and supersaturation enable this model to predict barite crystallization kinetics based only on the initial supersaturation and temperature. This study is a potential starting point to more quantitatively and comprehensively analyze and control mineral crystallization, important to various science and engineering applications.