Magnetocardiography is an advanced technique of measuring weak magnetic fields generated during heart functioning for diagnostics of huge number of different cardiovascular diseases. In this paper, k-nearest neighbor algorithm is applied for binary classification of myocardium current density distribution maps (CDDM). CDDMs from patients with negative T-peak, male and female patients with microvessels (diffuse) abnormalities and sportsmen are compared with normal subjects. Number of neighbors selection for k-NN classifier was performed to obtain highest classification characteristics. Specificity, accuracy, precision and sensitivity of classification as functions of number of neighbors in k-NN are obtained. Depending on group of heart state, accuracy in a range of 80–88%, 70–95% sensitivity, 78–95% specificity and 77–93% precision were achieved. Obtained results are acceptable for further patient's state evaluation.