Evidence on the lifetime risk for atherosclerotic cardiovascular disease (ASCVD) is insufficient; yet, estimating an individual’s lifetime risk allows for a comprehensive assessment of ASCVD burden. We developed and validated lifetime risk prediction equations for ASCVD using four large and ongoing prospective cohorts of Chinese, the China-PAR project (Prediction for ASCVD Risk in China). Sex-specific equations were developed using two cohorts (as the derivation cohort) of 21,320 participants. Two other independent cohorts with 14,123 and 70,838 participants were used for their external validation, respectively. We evaluated both calibration and discrimination measures for model performance. Furthermore, we estimated ASCVD-free years lost or excess absolute risk attributable to high 10-year risk (≥10.0%) and/or high lifetime risk (≥32.8%). After 12.3 years’ follow-up of the derivation cohort, 1048 ASCVD events and 1304 non-ASCVD deaths were identified. Our sex-specific equations had good internal validation, with discriminant C statistics of 0.776 (95% confidence interval [CI]: 0.757–0.794) and 0.801 (95% CI: 0.778–0.825), and calibration χ² of 9.2 (P = 0.418) and 5.6 (P = 0.777) for men and women, respectively. Good external validation was also demonstrated with predicted rates closely matched to the observed ones. Compared with men having both low 10-year and low lifetime risk, men would develop ASCVD 3.0, 4.6 and 8.6 years earlier if they had high 10-year risk alone, high lifetime risk alone, or both high 10-year and high lifetime risk at the index age of 35 years, respectively. We developed well-performed lifetime risk prediction equations that will help to identify those with the greatest potential to avert ASCVD burden after implementation of innovative clinical and public health interventions in China.