Stroke is a drawn-out incapacity illness caused everywhere on the world and it is the third driving reason for demise. Pre-syndromes of stroke dives more importance now a day. Stroke happened basically because of individual way of life in the cutting the edge period changing components, for example, high glucose, coronary illness, heftiness, diabetes. In this research, we analyse different Supervised machine Learning algorithms (i.e. SVC, DT, RFC, Logistic Regression, Linear Regression, Bernoulli NB, Gaussian NB and K-Nearest Neighbours Classifier). The accuracy in the work have found highest by applying Decision Tree classifier which is 0. 93.