Shelf stacking represents the daily process of manually refilling the shelves with products from new deliveries. For most retailers, handling operations are labour-intensive and often very costly. This paper presents an empirical study of the shelf-stacking process in grocery retail stores. We examine the complete process at the level of individual sub-activities and study the main factors that affect the execution time of this common operation. Based on the insights from different sub-activities, a prediction model is developed that allows estimating the total stacking time per order line, solely on the basis of the number of case packs and consumer units. The model is tested and validated using real-life data from two European grocery retailers and serves as a useful tool for evaluating the workload required for the usual shelf-stacking operations. Furthermore, we illustrate the benefits of the model by analytically quantifying the potential time savings in the stacking process, and present a lot-sizing analysis to demonstrate the opportunities for extending inventory control rules with a handling component.