In an era of immense technological advance, the resting ECG remains at the cornerstone of investigations for the evaluation and treatment of cardiovascular patients. In particular, the QT-interval duration has long been a metric of risk in focused areas such as mendelian long QT syndrome and in broader fields such as antiarrhythmic drug efficacy and toxicity. More broadly, the QT interval is a highly scrutinized metric of risk that strikes fear in the hearts of psychiatrists, primary care physicians, anesthetists, and pharmacists. This stems from recognized epidemiologic data that suggest the extent of QTc prolongation predicts both acute arrhythmic risk and long-term arrhythmic and nonarrhythmic mortality. Measuring and interpreting the QT interval remains a challenge despite the apparent wealth of data that should bring clarity. The need to correct the QT interval for heart rate has been recognized for nearly 100 years, yet the optimal means to do so remains a matter for discussion. The foundation for correction is the Bazett formula, first described 95 years ago! This well-established correction term is simple in concept, dividing the measured QT interval by the square root of the preceding RR interval (measured in seconds). The plot of the QT interval and the square root of the RR interval is linear at physiologic resting heart rates, showing a curvilinear shape at heart rates below 60 bpm and above 100 bpm. This leads to overcorrection of the QT interval at slow heart rates and undercorrection at high heart rates. Evaluating healthy cohorts with large-scale ECG screening generates rigorous population normative data that can be placed in the hands of thoughtful mathematicians. This leads to the development of alternate formulae that target a more linear correction across a broader RR interval spectrum. The first of these emerged virtually simultaneously with the Bazett formula, wherein the Fridericia derives the QT by the cube root of the RR interval, potentially improving discrimination at higher heart rates, while facing the same shortcomings at slow heart rates. Ideal formulas are often excessively complex, but several simplified formulas have