Risk assessment tools were developed to identify general population individuals at risks of future cardiac dysrhythmia and coronary heart disease (CHD) within the time period of one year using a dataset of EHRs obtained from Maine’s statewide Health Information Exchange. The prediction models were conditioned retrospectively and validated prospectively with AUC 0.827 and AUC 0.888. Our models were capable of prospectively stratifying the general population into five risk groups that were imminently likely to have a Cardiac Dysrhythmia incident and CHD. Our models may inform targeted care plans designed to manage patients at different levels of cardiac dysrhythmia and CHD risk.