Fine control of the enzymatic hydrolysis of cellulose is challenging due to complex process dynamics. Rate of conversion of cellulose to valuable monomeric products is often significantly slowed down after an initial rapid but short-lived phase. Underlying mechanisms for this process have yet to be fully understood and as a result poorly represented in existing models. Here, we propose a new modelling platform termed Multi-Layered Population Balance Model (ML-PBM), which enables various key aspects of cellulose enzymatic hydrolysis occurring over the entire breakdown process to be captured. As a core component for predicting the slowdown phenomenon, the ML-PBM properly accounts for heterogeneity in cellulose crystallinity and chain lengths across the structural layers of cellulose particles with different morphologies. Beyond a decent quantitative fit to highly nonlinear dynamic experimental data collected across different conditions, the ML-PBM reveals that the rate slowdown phenomenon is potentially due to heterogeneity in cellulose properties coupled with cellulose morphology. Equipped with the unification of various process fundamentals, the ML-PBM is a rational framework with the potential to facilitate sound cellulose engineering. (C) 2019 Elsevier Ltd. All rights reserved.