The objective of this study is to increase the understanding and transparency of chemical biotransfer modeling into meat and milk and explicitly confront the uncertainties in exposure assessments of chemicals that require such estimates. In cumulative exposure assessments that include food pathways, much of the overall uncertainty is attributable to the estimation of transfer into biota and through food webs. Currently, the most commonly used meat and milk-biotransfer models date back two decades and, in spite of their widespread use in multimedia exposure models, few attempts have been made to advance or improve the outdated and highly uncertain K(ow) regressions used in these models. Furthermore, in the range of K(ow) where meat and milk become the dominant human exposure pathways, these models often provide unrealistic rates and do not properly reflect the transfer dynamics. To address these issues, we developed a dynamic three-compartment cow model (called CKow), distinguishing lactating and nonlactating cows. For chemicals without available overall removal rates in the cow, a correlation is derived from measured values reported in the literature to predict this parameter from K(ow). Results on carry over rates (COR) and biotransfer factors (BTF) demonstrate that a steady-state ratio between animal intake and meat concentrations is almost never reached. For meat, empirical data collected on short-term experiments need to be adjusted to provide estimates of average longer term behaviors. The performance of the new model in matching measurements is improved relative to existing models-thus reducing uncertainty. The CKow model is straightforward to apply at steady state for milk and dynamically for realistic exposure durations for meat COR.