Scale and hierarchy have received less attention in aquatic systems compared to terrestrial. Walleye Sander vitreus spawning habitat offers an opportunity to investigate scale’s importance. We estimated lake-, transect-, and quadrat-scale influences on nearshore walleye egg deposition in 28 Minnesota lakes from 2016-2018. Random forest models (RFM) estimated importance of predictive variables to walleye egg deposition. Predictive accuracies of a multi-scale classification tree (CT) and a quadrat-scale CT were compared. RFM results suggested that five of our variables were unimportant when predicting egg deposition. The multi-scale CT was more accurate than the quadrat-scale CT when predicting egg deposition. Both model results suggest that in-lake egg deposition by walleye is regulated by hierarchical abiotic processes and that silt/clay abundance at the transect-scale (reef-scale) is more important than abundance at the quadrat-scale (within-reef). Our results show machine learning can be used for scale-optimization and potentially to determine cross-scale interactions. Further incorporation of scale and hierarchy into studies of aquatic systems will increase our understanding of species-habitat relationships, especially in lentic systems where multi-scale approaches are rarely used.