Solid tumors and other pathologies can be treated using laser thermal ablation under interventional magnetic resonance imaging (iMRI) guidance. We developed a model to predict cell death from MR thermometry measurements and applied it to in vivo rabbit brain data. To align post-ablation T2-weighted spin-echo MR lesion images to gradient echo MR images, from which temperature is derived, we used a registration method that aligned fiducials placed near the thermal lesion. We used the outer boundary of the hyperintense rim in the post-ablation MR lesion image as the boundary for cell death, as verified from histology. Model parameters were simultaneously estimated using an iterative optimization algorithm applied to every interesting pixel in 328 images from multiple experiments having various temperature histories. For a necrotic region of 766 voxels across all lesions, the model gave a voxel specificity and sensitivity of 98.1% and 78.4%, respectively. Median distance between the segmented necrotic boundary and the mislabeled voxels was within one MR voxel. Furthermore, our model predicted fewer errors as compared to the critical temperature cell death model. This is good evidence that iMRI temperature maps can be used with our model to predict therapeutic regions in real-time.