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Directional deep brain stimulation (dDBS) of the subthalamic nucleus for Parkinson's disease (PD) increases the therapeutic window. However, empirical programming of the neurostimulator becomes more complex given the increasing number of stimulation parameters. A better understanding of dDBS is needed to improve therapy and help guide postoperative programming. To determine whether clinical effects of dDBS can be predicted in individual patients based on lead location and volume of tissue activated (VTA) modelling. We analysed a prospective series of 28 PD patients. Imaging analysis and systematic clinical testing performed 4–6 months postoperatively yielded location, clinical efficacy and corresponding therapeutic windows for 272 directional contacts. We calculated the corresponding VTAs to build a probabilistic stimulation map using voxel-wise statistical analysis. We found a positive and statistically significant correlation between the overlap ratio of a patient's individual stimulation volume and the probabilistic map's sweet spot –defined as the 10% voxels with the highest clinical efficacy values (average Spearman's rho = 0.43, average p ≤ 0.036). Patients who had a larger therapeutic window with directional compared to omnidirectional stimulation had a larger distance between the electrode and the sweet spot centroid (average distances 2.3 vs. 1.5 mm, p = 0.0019). Our analysis provides new insights into how the definition of a probabilistic sweet spot based on directional stimulation data and individual VTA modelling can be applied to predict clinically effective directional stimulation and help guide clinicians with the intricate postoperative DBS programming. • The probabilistic sweet spot for directional stimulation projected onto the dorsolateral STN. • Overlap ratio of individual stimulation volume and sweet spot correlated with clinical efficacy. • Overlap ratio and distance to the sweet spot were indicators of efficient directional stimulation. [ABSTRACT FROM AUTHOR]