We compared mean intra-arterial ambulatory blood pressure (IAMB), blood pressure (BP) diurnal profiles are variability, and postural measurements with casual sphygmomanometric measurements for the prediction of future BP. We studied 97 healthy, ummedicated men classified as normotensive (NT, n = 34), borderline hypertensive (BHT, n = 29), or mildly hypertensive (HT, n = 34) by repeated casual measurements during the 2 months before IAMB. Five years later, we reassessed 79 subjects (81%) using casual BP measurements and noninvasive ambulatory 24-hour BP monitoring (NAMB). IAMB level generally correlated well with follow-up BP and slightly better with NAMB level than with casual measurements (24-hour IAMB versus follow-up NAMB systolic BP [SBP], r = .64, P < .001; versus diastolic' BP [DBP], r = .52, P < .001). NT and BHT subgroup correlations were of similar strength, but the relationship in the HT subgroup was not significant. Similarly, when we examined daytime and nighttime BP levels, nighttime BP correlated better with follow-up BP in NT and BHT but not in HT. The only measures that were significantly related to follow-up BP in HT were two BP variability measures, SD and the range of variability (RV80: 90th minus 10th percentile), (initial 24-hour IAMB SD and follow-up BP, r = .42 to r = .52, P < .05 to P < .01; RV80 versus follow-up BP, r = .43 to r = .52, P < .05 to P < .01). Correlations of follow-up BP with postural BP were generally weaker than with casual BP or IAMB level. Linear stepwise regressions for SBP and DBP separately (including all IAMB variables) demonstrated that the best single predictor for follow-up BP was 24-hour IAMB SBP level, which explained 41% of follow-up NAMB SBP level variance (F = 52.6, P < .001). However, in a second analysis including casual values, casual SBP alone explained 44% of follow-up NAMB SBP variance (F = 62.5, P < .001), whereas IAMB SBP added only 4% (F = 5.5, P < .05). Predictions of follow-up DBP were always poorer. After 5 years, 70% of NT and 86% of HT were still in their initial classification group, but 67% of BHT had become hypertensive. In these new HT (n = 16), initial IAMB level correlated most strongly with follow-up NAMB level (24-hour SBP, r = .70, P < .01; 24-hour DBP, r = .55, P < .05). The only other significant demographic variable predicting future BP was change in weight over 5 years, which added 10% to the explanation of future casual SBP variance (F = 12.5, P = .0007) and 15% to casual DBP variance (F = 18.0, P = .0001); for NAMB, the percentages were lower. In logistic regression, those NT and BHT who became hypertensive (n = 22) had a 75% probability of becoming hypertensive if they gained 11.7 kg or more during 5 years (X2 = 4.5, P = .03). To conclude, BP tended to increase in all groups, especially in BHT, during follow-up. Nominal differences were observed between casual measurements and BP level measures in the prediction of future BP, and their explanatory value for future BP was generally less than 50%. However, for BHT who became hypertensive, BP level and variability measurements somewhat improved the prediction of follow-up BP. Weight gain was an important additional predictor for future hypertension in both NT and BHT.