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This study examines the viability of utilizing a dynamical system model and heuristic parameter estima-tion algorithm to make predictions for maximum heart rate _ 2max ) using data (HR max ) and maximal oxygen uptake ( VO _ 2max is
collected from a submaximal testing protocol. VO widely considered to be the best single measurement of _ 2max assessment is overall fitness in humans. When a VO not available, HR max is often used to prescribe exercise intensities for training and rehabilitation. In the absence of maximal cardio pulmonary exercise testing (CPET), HR max _ 2max are typically estimated using traditional sub-and VO maximal prediction methods with well-known limitations and inaccuracies. or this study, 12 regularly exercising healthy young adult males performed a bout of maximal CPET on a cycle ergometer to determine their true HR max _ 2max . Participants also performed a submaximal and VO bout of exercise at varied intensities. A dynamical system model and heuristic parameter estimation algorithm were applied to the submaximal data to estimate the participants’ _ 2max . The submaximal predictions were HR max and VO evaluated by computing the coefficient of determination R 2 and the standard error of the estimate (SEE) through comparisons with the true maximal values for HR max _ 2max (R 2 1⁄4 0:93, SEE (R 2 1⁄4 0:96, SEE = 2.4 bpm) and VO = 2.1 mL kg .1 min .1 ). The results from this study suggest that a dynamical system model and heuristic parameter estimation algorithm can provide accurate predictions for _ 2max using data collected from a submaximal HR max and VO testing protocol.