PURPOSE: The aim of the study was to investigate whether a statistical model could be used for an early prediction of the head-up tilt test (HUTT) outcome from heart rate variability (HRV) and baroreflex sensitivity (BRS) data obtained during early stages of the HUTT. METHODS: A modified Italian protocol was used for HUTT in 105 patients with a previous history of vasovagal syncope. Beat-to-beat heart rate and blood pressure were continuously recorded. Fast Fourier transformation was used for spectral analysis of HRV and a sequence technique for measuring the BRS. RESULTS: Linear statistical models based on HRV and BRS data from the first 15 min of HUTT were no more accurate than always naively predicted majority class that a syncope will occur (average model out-of-sample accuracy 56.2 +/- 5.1 % vs. majority class relative frequency 54.2 %). Even when HRV and BRS data from the first 30 min were used in the model, we did not obtain any predictions of meaningful practical value (75.0 +/- 5.1 % accuracy vs. 72.2 % majority class). CONCLUSIONS: While there are discernible and meaningful differences between HUTT-P and HUTT-N subjects, they are not sufficient to discriminate between the two groups and predict a syncope early in the HUTT. The results might improve with a larger set of subjects; however, we can conclude that it is not likely that syncope predictions of practical value can be obtained from aggregate HRV spectral analysis and BRS values.