Ultrasensitive prostate-specific antigen (u-PSA) remains controversial for follow-up after radical prostatectomy (RP). The aim of this study was to model PSA doubling times (PSADT) for predicting biochemical recurrence (BCR) and to capture possible discrepancies between u-PSA and traditional PSA (t-PSA) by utilizing advanced statistical modeling. 555 RP patients without neoadjuvant/adjuvant androgen deprivation from the Turku University Hospital were included in the study. BCR was defined as two consecutive PSA values >0.2 ng/mL and the PSA measurements were log2-transformed. One third of the data was reserved for independent validation. Models were first fitted to the post-surgery PSA measurements using cross-validation. Major trends were then captured using linear mixed-effect models and a predictive generalized linear model effectively identified early trends connected to BCR. The model generalized for BCR prediction to the validation set with ROC-AUC of 83.6% and 95.1% for the 1 and 3 year follow-up censoring, respectively. A web-based tool was developed to facilitate its use. Longitudinal trends of u-PSA did not display major discrepancies from those of t-PSA. The results support that u-PSA provides useful information for predicting BCR after RP. This can be beneficial to avoid unnecessary adjuvant treatments or to start them earlier for selected patients.