We have used Monte Carlo methods to study the sensitivity and uncertainty of heat exchanger designs to physical properties estimation. The determination of appropriate confidence intervals for the overall heat-transfer coefficient and total required heat-exchange area plays a very important role in heat-exchanger thermal designs. The physical property models used exhibit systematic and random errors, which can change depending on how the models are used. Of particular interest in this work were the errors in properties estimation at high temperatures. Experimental physical properties of hot-gas mixtures at high temperatures (i.e., combustion gases) are very limited, and heat-exchanger simulation and design relies heavily on predictive models for physical properties. In this work, case studies of heat-exchanger performance and design under the influence of random and systematic errors on property estimation are presented. The results show that the performance and design can be very sensitive to errors in physical properties. The analysis method proposed can be used to identify when and which, properties play a significant role in the error propagation for this type of equipment. Further, the methodology proposed can be used to study the uncertainty in heat-exchanger performance and cost introduced by these types of errors.