Cryosurgery is a medical technique that uses a freezing process to destroy undesirable tissues such as cancerous tumors. The handheld portion of the cryoprobe must be compact and powerful in order to serve as an effective surgical instrument; the next generation of cryoprobes utilizes precooled Mixed Gas Joule–Thomson (pMGJT) cycles to meet these design criteria. The increased refrigeration power available with this more complex cycle improves probe effectiveness by reducing the number of probes and the time required to treat large tissue masses. Selecting mixtures and precooling cycle parameters to meet a cryogenic cooling load in a size-limited application is a challenging design problem. Modeling the precooler and recuperator performance is critical for cycle design, yet existing techniques in the literature typically use highly idealized models of the heat exchangers that neglect pressure drop and assume infinite conductance. These assumptions are questionable for cycles that are required to use compact components. The focus of this research project is to understand how the cycle performance is impacted by transport processes in the heat exchangers and to integrate these findings into an empirically tuned model that can be used for mixture optimization. This effort is carried out through a series of modeling, experimental, and optimization studies. While these results have been applied to the design of a cryosurgical probe, they are also more generally useful in understanding the operation of other compact MGJT systems. A commercially available pMGJT cryoprobe system has been modified in order to integrate a suite of measurement instrumentation that can completely characterize the performance of the individual components as well as the overall system. Measurements include sufficient temperature and pressure sensors to resolve thermodynamic states, as well as flow meters in order to compute the heat and work transfer rates. Temperature sensors are also integrated within the recuperator in order to capture the spatially resolved heat transfer performance; these data are used to overcome the lack of correlations for heat transfer of the multi-phase mixture in the helically wound finned-tube heat exchanger. Test conditions were varied to achieve a range of temperatures, pressures, and thermodynamic qualities with mixtures of argon, R14 and R23. Recuperator and precooler conductance and pressure drop data for these test conditions are presented and fit to simple physics-based correlations; these correlations are integrated with an optimization model of the precooled MGJT cryoprobe that has been described in a previous paper. The predictive capabilities and optimal mixture selections of the model are compared with those of other models available in the literature, including the isothermal enthalpy difference model.