Using first-order statistical features, this paper presents a new method for detecting Alzheimer's disease (AD) in 3D brain Magnetic Resonance images. Alzheimer's disease is a neurological condition that mostly affects the elderly. Because Alzheimer's disease is a progressive disease, early detection and classification can greatly aid in disease management. Recent research has used voxel-based Magnetic Resonance brain image feature extraction approaches in conjunction with machine learning algorithms to achieve this goal. Because Alzheimer's disease alters and damages the grey and white matter of the brain, their study has proven to be more successful in predicting the condition. The proposed method separates Magnetic Resonance images of white and grey matter from 3D structural brain Magnetic Resonance images, generating 2D coronal slices.