The data workflow described in this technical report offers a predictive model for the construction of size charts using statistical learning techniques. This is in contrast to previous researchers who have only employed descriptive and exploratory statistics to summarize various body measurements to construct size charts to support garment fit. The garment size charts constructed by this research are designed to support stock management decisions rather then garment comfort. The size chart measurements identified by the statistical model were identified by applying a regression model to 800 female subjects; whose measurements were obtained by computer vision technology. The research discovered that the regression model is sensitive to body shape and that more accurate body measurements are predicted when the body measurement data set of subjects has been separated into body shape/height subgroups.