||For magnetic resonance-guided focused ultrasound (MRgFUS) treatments to be broadly accepted, progress must be made in treatment planning, monitoring, and control. A key component to this goal is accurate modeling of the bioheat transfer equation (BHTE). This dissertation develops new methods for identifying the significant parameters of the BHTE: the ultrasonic specific absorption rate (SAR), the tissue thermal diffusivity, and perfusion-related energy losses. SAR is determined by fitting an analytical solution one-dimensional radial Gaussian heating) to MRgFUS temperature data in simulations and a tissue-mimicking phantom. This new method is compared with linear and exponential methods for different fitting times, beam sizes, perfusion, and thermal diffusivity values. The analytical method is consistently most reliable and is accurate to within 10% for all cases, except high perfusion. An extension to the analytical solution improves SAR estimates for high perfusion cases. MRgFUS sampling characteristics (spatial averaging, temporal sampling, and noise) for SAR and thermal diffusivity estimation are parametrically evaluated against several focused ultrasound beam sizes. For single point heatings, a maximum voxel size of 1x1x3 mm is recommended for temperature and estimate errors to remain less than 10%. Two MRgFUS thermal diffusivity estimation methods are evaluated against a standard technique in ex vivo porcine and in vivo rabbit back muscle. Both methods accurately estimate thermal diffusivity using cooling data (overall ex vivo error < 6%, in vivo < 12%). Including heating data in the Gaussian SAR method further reduces errors (ex vivo error < 2%, in vivo < 3%). The Gaussian SAR method has better precision than the Gaussian temperature method. Two methods for quantifying perfusion-related energy losses using MRgFUS cooling temperatures are developed (experimental + modeled data vs. experimental data). The methods are verified via simulations and experiments in ex vivo perfused porcine kidney at different flow rates. The difference techniques employed make these methods susceptible to noise errors, but this feasibility study demonstrates promise for their use in future work. In conclusion, these methods can be used to validate biothermal models, and associated improvements in thermal modeling have the potential to increase the efficacy and safety of MRgFUS therapies.