Until recently, there has been a focus on exploring the influence of average blood pressure (BP) on risk of mortality. We go beyond average BP to also investigate mortality risk with respect to variation in BP over 2 timescales—short-term variation among multiple measures at 1 visit, and medium-term variation among the measures at 2 visits several months apart. We present an application of Bayesian hierarchical modeling to the problem of estimating the effect of BP variability on all-cause and cardiovascular mortality. We use data from the Third National Health and Nutrition Examination Survey linked with up to 27 years of mortality follow-up. We find that medium-term systolic BP variability had a very significant predictive value for all-cause mortality in addition to mortality from cardiovascular disease, cerebrovascular disease and heart-attacks combined, approximately 1/3 as large as the well-established impact of mean systolic BP. Medium-term diastolic variability had an additional, although smaller, predictive effect. Short-term variability, in contrast, had little or no measurable predictive value. The medium-term variability effect persisted when controlling for Framingham Risk Score.