Blood potassium concentration ([K⁺]) influences the electrocardiogram (ECG), particularly T-wave morphology. We developed a new method to quantify [K⁺] from T-wave analysis and tested its clinical applicability on data from dialysis patients, in whom [K⁺] varies significantly during the therapy. To elucidate the mechanism linking [K⁺] and T-wave, we also analysed data from long QT syndrome type 2 (LQT2) patients, testing the hypothesis that our method would have underestimated [K⁺] in these patients. Moreover, a computational model was used to explore the physiological processes underlying our estimator at the cellular level. We analysed 12-lead ECGs from 45 haemodialysis and 12 LQT2 patients. T-wave amplitude and downslope were calculated from the first two eigenleads. The T-wave slope-to-amplitude ratio (T_S/A) was used as starting point for an ECG-based [K⁺] estimate (K_ECG). Leave-one-out cross-validation was performed. Agreement between K_ECG and reference [K⁺] from blood samples was promising (error: -0.09 ± 0.59 mM, absolute error: 0.46 ± 0.39 mM). The analysis on LQT2 patients, also supported by the outcome of computational analysis, reinforces our interpretation that, at the cellular level, delayed-rectifier potassium current is a main contributor of K_ECG correlation to blood [K⁺]. Following a comprehensive validation, this method could be effectively applied to monitor patients at risk for hyper/hypokalemia.