The article explores the concept of aging clocks, which are indicators of biological age and the effectiveness of interventions in aging processes. The authors demonstrate that accumulating stochastic variation in simulated data is sufficient to build accurate aging clocks, regardless of the type of biological measurement used. They show that first-generation and second-generation aging clocks are compatible with the accumulation of stochastic variation in DNA methylation or transcriptomic data. The study finds that stochastic variation is sufficient to predict chronological and biological age, as indicated by significant differences in aging outcomes such as smoking, calorie restriction, heterochronic parabiosis, and partial reprogramming. The results suggest that aging clocks can be based on any biological parameter with stochastic age-related alterations, without the need for a deterministic process. The authors also validate their findings using real-world data from the Mammalian Methylation Consortium, showing that aging clocks can accurately predict chronological and biological age across various mammalian species and interventions. The study concludes that aging clocks measure the accumulation of stochastic variation, providing a robust framework for understanding and predicting aging processes.The article explores the concept of aging clocks, which are indicators of biological age and the effectiveness of interventions in aging processes. The authors demonstrate that accumulating stochastic variation in simulated data is sufficient to build accurate aging clocks, regardless of the type of biological measurement used. They show that first-generation and second-generation aging clocks are compatible with the accumulation of stochastic variation in DNA methylation or transcriptomic data. The study finds that stochastic variation is sufficient to predict chronological and biological age, as indicated by significant differences in aging outcomes such as smoking, calorie restriction, heterochronic parabiosis, and partial reprogramming. The results suggest that aging clocks can be based on any biological parameter with stochastic age-related alterations, without the need for a deterministic process. The authors also validate their findings using real-world data from the Mammalian Methylation Consortium, showing that aging clocks can accurately predict chronological and biological age across various mammalian species and interventions. The study concludes that aging clocks measure the accumulation of stochastic variation, providing a robust framework for understanding and predicting aging processes.