Although EPA [1] recommends that exposures associated with the consumption of home-grown produce be evaluated in human health risk assessments, the Agency does not provide specific guidance for quantitatively assessing inorganic uptake by plants. In the absence of site-specific data, risk assessors are forced to rely on the use of various predictive methods to quantitatively evaluate the contribution of produce ingestion to total daily intake. The concentration of metals in plants is typically estimated by multiplying the total concentration of metal in soil by a metal-specific soil-to-root uptake factor (RUF). Metal-specific RUFs were calculated using measured soil and plant data collected during the remedial investigation for the Globe Plant (a smelter) in Colorado. These RUFs are compared to values reported by Baes et al. [2]. Results show that RUFs reported by Baes et al. [2] may underestimate the concentration of As, Cd, and Pb in garden crops. Using the concentration of metal in soil to predict the concentration of metal in plants does not account for various soil properties, such as pH, organic matter content, and cation exchange capacity, that are known to influence root uptake of metals. Multiple linear regression analyses were used to develop simple, predictive models for estimating the concentration of metals in home-grown vegetables. This paper presents preliminary predictive equations for estimating root uptake of As, Cd, Cu, and Zn in fruiting and root vegetables to draw attention to this issue, so that the importance of this pathway and subsequent influence on human exposure can be more accurately assessed. Results show that by using data on additional soil parameters (other than relying solely on the concentration of metal in soil), the concentration of metals in fruiting and root vegetables can be more confidently predicted.