Older adults are more risk-averse than younger adults especially under age-related stereotypes (Barber, 2017), yet the underlying mechanism remains unclear. This study examined the impact of positive and negative age-related stereotypes on risk decisions and dissected cognitive dimensions through computational modeling. Ninety-four older adults (M = 67.20, SD = 4.88) were randomly assigned to receive information either containing positive or negative age-related stereotypes or the same neutral information as 32 younger adults (M = 20.16, SD = 1.27) received. Participants then completed the Balloon Analogue Risk Task. Computational models were applied to analyze cognitive dimensions. Results indicated significant age differences in learning rates. Moreover, older adults receiving positive stereotypes hold lower prior beliefs of risk compared to those receiving negative and neutral information, and were more risk averse than younger adults. Discussion emphasized how computational models can advance the understanding of cognitive underpinnings in risk decision-making under age-related stereotypes.