Agglomeration of fine mineral particles as a precursor to heap leaching is an important means of enhancing leaching rates and metal recoveries, particularly in processing low grade laterite ores. To fully understand the underlying mechanisms and kinetics of agglomeration, it is necessary to establish a useful, predictive model based on feed and product characteristics (e.g., size and structure analyses), for better design and control of the agglomeration processes. Useful rate parameters of the mechanisms and kinetics may be extracted from appropriate agglomeration experiments and used for the optimization and scale-up and also the benchmarking of our understanding on real ore agglomeration processes. In this paper, the modelling of the batch drum agglomeration process of selected clay and oxide mineral ores (hematite, quartz, kaolinite and smectite) using a population balance model is explored. The coalescence kernels which are linked to batch granulator operating conditions are reviewed. One-dimensional population balance modelling approach is developed based on the results of single minerals. The use of a physically based coalescence kernel shows a great promise for the modelling of the granule size distribution of single minerals and both the fundamental material properties and the operating conditions are linked to the model