It is well accepted in Cryobiology that the temperature history and cooling rates experienced in biomaterials during freezing procedures correlate strongly with biological outcome. Therefore, heat transfer measurement and prediction in the cryogenic regime is central to the field. Although direct measurement of heat transfer can be performed, accuracy is usually achieved only for local measurements within a given system and cannot be readily generalized to another system without the aid of predictive models. The accuracy of these models rely upon thermal properties which are known to be highly dependent on temperature, and in the case of significant cryoprotectant loading, also on crystallized fraction. In this work we review the available thermal properties of biomaterials in the cryogenic regime. The review shows a lack of properties for many biomaterials in the subzero temperature domain, and especially for systems with cryoprotective agents. Unfortunately, use of values from the limited data available (usually only down to −40 °C) lead to an underestimation of thermal property change (i.e. conductivity rise and specific heat drop due to ice crystallization) with lower temperatures. Conversely, use of surrogate values based solely on ice thermal properties lead to an overestimation of thermal property change for most biomaterials. Additionally, recent work extending the range of available thermal properties to −150 °C has shown that the thermal conductivity will drop in both PBS and tissue (liver) due to amorphous/ glassy phases (vs. ice) of biomaterials with the addition of cryoprotective additives such as glycerol. Thus, we investigated the implications of using approximated or constant property values versus measured temperature-dependent values for predicting heat transfer in PBS (phosphate buffered saline) and porcine liver with and without cryoprotectants (glycerol). Using measured property values (thermal conductivity, specific heat, and latent heat of phase change) of porcine liver, a standard was created which showed that values based on surrogate ice properties underpredicted cooling times, while constant properties (i.e. based on limited data reported near the freezing point) over-predicted cooling times. Additionally, a new iterative numerical method that accommodates non-equilibrium cooling effects as a function of time and position (i.e. crystallization vs. amorphous phase) was used to predict heat transfer in glycerol loaded systems. Results indicate that in addition to the increase in cooling times due to the lowering of thermal © 2009 Elsevier Inc. All rights reserved.Correspondence to: John C. Bischof. Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors ma...