Abstract: The establishment of a leaf growth prediction model in forestry, ecology and botany has been the focus of attention and difficulty. We measured leaf length, leaf width, SPAD (S) value of Ipomoea batatas and used their combination to develop 10 regression models to predict individual leaf area (LA), saturated fresh weight (SFW), and dry weight (DW) of I. batatas. We selected the best-fit model as a predictive model for LA, SFW and DW. Three models were LA=–22.995+5.322W+0.322L² (R=0.972), SFW=0.459+0.000 034 1LWS (LWS: Leaf length×Leaf width×SPAD)(R= 0.964), and DW=–0.064+0.016W+0.000 048 4LS (LS: Leaf length×SPAD)(R=0.955). We validated the best prediction models with the measured value. The predicted and measured values were highly consistent (R²>0.9, P<0.001). The models could be used to predict LA, SFW and DW of actual unknown leaves. We therefore provide model for simplifying the determination of plant leaf traits.