Background: The classic electrocardiogram (ECG) criteria have been applied to left ventricular hypertrophy (LVH) screening but have low sensitivity. Recently, the newly proposed Peguero-Lo Presti criterion has been proven to be more sensitive in detecting LVH in patients with hypertension than several current ECG criteria. The diagnostic value of the Peguero-Lo Presti criterion in hypertrophic cardiomyopathy (HCM) patients has not been fully evaluated. This study aims to test whether the new Peguero-Lo Presti criterion can improve the diagnostic performance in patients with HCM. Methods: This study included HCM patients and sex-and age-matched healthy control subjects. The diagnostic performance of the Peguero-Lo Presti criterion was evaluated along with the Sokolow-Lyon criterion, Cornell criterion, and total 12-lead voltage criterion. Results: Overall, 63 HCM patients and 63 controls were enrolled. The diagnostic accuracy, sensitivity and specificity of Peguero-Lo Presti criterion were 74.6%, 73.0% and 76.2%, respectively. The Peguero-Lo Presti criterion had the highest sensitivity, while the Cornell criterion and Sokolow-Lyon criterion had the highest specificity (96.8%). The area under the curve (AUC) showed that the Peguero-Lo Presti criterion was 0.809 (95% CI, 0.730–0.874; p 0.0001), Sokolow-Lyon criterion was 0.841 (95% CI, 0.766–0.900) and total 12-lead voltage criterion was 0.814 (95% CI, 0.735–0.878). There was no significant difference in AUC between Peguero-Lo Presti criterion and Sokolow-Lyon criterion (p = 0.533), or Peguero-Lo Presti criterion and total 12-lead voltage criterion (p = 0.908). Receiver operator characteristic curve analysis of the Peguero-Lo Presti criterion showed an optimal cutoff of >3.15 mV for men (sensitivity: 63.9%; specificity: 80.0%) and >2.29 mV for women (sensitivity: 78.6%; specificity: 85.7%). Conclusions: The Peguero-Lo Presti criterion provides high sensitivity for ECG diagnosis of HCM patients and can be considered when applicable but this needs to be verified in a larger population.