For a study, researchers sought to collect individual clinical and neuroimaging data from patients having deep brain stimulation (DBS) for essential tremor (ET) at 5 different centers to find predictors of outcome and the best stimulation site. They investigated retrospectively baseline variables, pre-and postoperative clinical tremor scores (for 12 months), and individual imaging data from 119 patients to acquire individual electrode placements and stimulation volumes. A probabilistic simulation map in normalized space was constructed using individual imaging and clinical data using voxel-wise statistical analysis. Finally, the map was utilized to build a classifier that might predict tremor improvement. The statistically significant cluster associated with a tremor improvement of more than 50% was discovered using probabilistic mapping of stimulation effects. This cluster of optimum stimulation ran from the posterior subthalamic area to the ventralis intermedius nucleus, and it corresponded to a cerebellothalamic tract (CTT) with a normal anatomical connection. As a predictor of tremor improvement, the variables “distance between the stimulation volume and the significant cluster” and “CTT activation” were combined. A sensitivity of 89% and a specificity of 57%, accurately detected a more than 50% tremor improvement. Along the course of the CTT, our multicenter ET probabilistic stimulation map found an area of optimal stimulation. The study outcomes were mostly descriptive until they were verified in other datasets, preferably by prospective testing. The target will be made publicly available and may be utilized in the future to guide surgical planning and computer-assisted DBS programming.