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As a clinical syndrome, Dementia causes one’s cognitive functionlowering in multiple areas, such as memory, language, and judgment and thereby prevents one’s activities of daily living. As dementia cases are rising globally, it is required to devise a model that can predict it’s occurrence well in advance so that it’s progression can be delayed. Magnetic Resonance Imaging (MRI) is a non-invasive technique that can be used to diagnose and measure various brain disorders. In this paper, a machine learning model usingensemble bagging trees is proposed.It is validated using publicly available Open Access Series of Imaging Studies (OASIS) dataset.When the proposed model is compared with Logistic Regression,Decision Tree and Support Vector Machine (SVM), it has the best performance with an accuracy of 97.8%.