Predictive modeling is crucial because it saves time and resources compared to traditional trial-and-error methods. It allows researchers to screen potential catalysts efficiently, identify optimal operating conditions, and understand the underlying mechanisms of catalytic reactions. This accelerates the development of new catalysts and the improvement of existing ones.
