Purpose: Although several clinical nomograms predictive of biochemical failure-free survival (BFFS) for localized prostate cancer exist in the medical literature, making valid comparisons can be challenging due to variable definitions of biochemical failure, the disparate distribution of prognostic factors, and received treatments in patient populations. The aim of this investigation was to develop and validate clinically-based nomograms for 5-year BFFS using the ASTRO II “Phoenix” definition for two patient cohorts receiving low-dose rate (LDR) brachytherapy or conventionally fractionated external beam radiation therapy (EBRT) from a large Canadian multi-institutional database.Methods and Materials: Patients were selected from the GUROC (Genitourinary Radiation Oncologists of Canada) Prostate Cancer Risk Stratification (ProCaRS) database if they received (1) LDR brachytherapy ≥ 144 Gy (n=4208) or (2) EBRT ≥ 70 Gy (n=822). Multivariable Cox regression analysis for BFFS was performed separately for each cohort and used to generate clinical nomograms predictive of 5-year BFFS. Nomograms were validated using calibration plots of nomogram predicted probability versus observed probability via Kaplan-Meier estimates.Results: Patients receiving LDR brachytherapy had a mean age of 64 ± 7 years, a mean baseline PSA of 6.3 ± 3.0 ng/mL, 75% had a Gleason 6, and 15% had a Gleason 7, whereas patients receiving EBRT had a mean age of 70 ± 6 years, a mean baseline PSA of 11.6 ± 10.7 ng/mL, 30% had a Gleason 6, 55% had a Gleason 7, and 14% had a Gleason 8-10. Nomograms for 5-year BFFS included age, use and duration of androgen deprivation therapy (ADT), baseline PSA, T stage, and Gleason score for LDR brachytherapy and an ADT (months), baseline PSA, Gleason score, and biological effective dose (Gy) for EBRT.Conclusions: Clinical nomograms examining 5-year BFFS were developed for patients receiving either LDR brachytherapy or conventionally fractionated EBRT and may assist clinicians in predicting an outcome. Future work should be directed at examining the role of additional prognostic factors, comorbidities, and toxicity in predicting survival outcomes.