At present, there are no useful methods for monitoring fatigue accumulation during training exercises. Excess Post-exercise Oxygen Consumption (EPOC) after exercise is the greater the more exhausting the exercise. PURPOSE: To pre-predict the amount of EPOC measured after exercise from information recorded before and during exercise. METHODS: Based on meta-analysis of 48 peer-reviewed studies including 158 subjects in different exercise settings (duration and intensity ranging from 2 to 90 minutes and 18% to 108% of VO2max, respectively) a computational model based on heart function (patent pending) for pre-predicting EPOC (EPOCpred) was constructed. A total of 32 healthy adult subjects (16 males, 16 females) with age of 38 ± 9 years (mean ± SD), weight 69.6 ± 10.8 kg, height 171.6 ± 8.5 and VO2max 44.0 ± 8.8 ml/kg•min, served as a separate validation set. Subjects carried out two 10-min constant load exercises at intensities of 40% and 70% VO2max and a maximal stepwise test to voluntary exhaustion. EPOCpred was pre-predicted from ECG RR-interval data collected with Polar RR-recorder. After exercises 15-min EPOC was measured (EPOCmeas) using Vmax analyzer (Sensor Medics). RESULTS: EPOCpred vs. EPOCmeas in 40%, 70% and maximal test conditions were 0.45 ± 0.21 vs. 0.96 ± 0.88 l (p<0.05), 1.94 ± 0.73 vs. 2.05 ± 1.06 l (ns), and 5.91 ± 1.64 vs. 6.28 ± 1.52 l (ns), respectively. Correlations between EPOCpred and EPOCmeas and Mean Absolute Error over all exercises and for maximal exercise were r = 0.889 (p<0.001) and 0.612 (p<0.001), and MAE = 0.96 l and 1.17 l, respectively. CONCLUSION: EPOC can be pre-predicted from RR interval data recorded during exercise. Consequently, EPOC pre-prediction may serve as a tool for monitoring fatigue accumulation during exercise.