Dopamine receptors are of particular importance in the pathophysiology of CNS disorders and thus, serve as promising target proteins for the discovery of new chemical entities. For this purpose quantitative structure activity relationship (QSAR) modelling has been traditionally applied as an evaluative approach, with the focus on developing retrospective and explanatory models of existing data. To obtain a more detailed insight into the structure activity relationship for reported Dopamine D2 antagonist, pharmacophore was identified through molecular alignment and employed in three-dimensional (3D) QSAR studies. 3D QSAR model developed considering training and test set approaches with step wise variable selection method. QSAR models which were further validated for statistical significance and predictive ability by internal and external validation. The selected best QSAR model A has training set of 18 molecules and test set of 9 molecules with the correlation coefficient of 0.9670. The predictive power of the derived model was demonstrated to be very high. Graphical interpretation of the results brings to the light, important structural features of the compound related to either low or high-affinity dopamine antagonism. Electrostatically favourable and unfavourable regions were identified. The results of the 3D QSAR studies indicate that bulky N-substituents decrease D2 binding. Electrostatically favourable and unfavourable regions exclusive to D2 receptor binding were identified. These observations may be exploited for the design of novel dopamine D2 antagonists.