Prostate-specific membrane antigen (PSMA)–targeting PET imaging is becoming the reference standard for prostate cancer staging, especially in advanced disease. Yet, the implications of PSMA PET–derived whole-body tumor volume for overall survival are poorly elucidated to date. This might be because semiautomated quantification of whole-body tumor volume as a PSMA PET biomarker is an unmet clinical challenge. Therefore, in the present study we propose and evaluate a software that enables the semiautomated quantification of PSMA PET biomarkers such as whole-body tumor volume. The proposed quantification is implemented as a research prototype. PSMA-accumulating foci were automatically segmented by a percental threshold (50% of local SUV_max). Neural networks were trained to segment organs in PET/CT acquisitions (training CTs: 8,632, validation CTs: 53). Thereby, PSMA foci within organs of physiologic PSMA uptake were semiautomatically excluded from the analysis. Pretherapeutic PSMA PET/CTs of 40 consecutive patients treated with ¹⁷⁷Lu-PSMA-617 were evaluated in this analysis. The whole-body tumor volume (PSMA_TV50), SUV_max, SUV_mean, and other whole-body imaging biomarkers were calculated for each patient. Semiautomatically derived results were compared with manual readings in a subcohort (by 1 nuclear medicine physician). Additionally, an interobserver evaluation of the semiautomated approach was performed in a subcohort (by 2 nuclear medicine physicians). Manually and semiautomatically derived PSMA metrics were highly correlated (PSMA_TV50: R² = 1.000, P < 0.001; SUV_max: R² = 0.988, P < 0.001). The interobserver agreement of the semiautomated workflow was also high (PSMA_TV50: R² = 1.000, P < 0.001, interclass correlation coefficient = 1.000; SUV_max: R² = 0.988, P < 0.001, interclass correlation coefficient = 0.997). PSMA_TV50 (ml) was a significant predictor of overall survival (hazard ratio: 1.004; 95% confidence interval: 1.001–1.006, P = 0.002) and remained so in a multivariate regression including other biomarkers (hazard ratio: 1.004; 95% confidence interval: 1.001–1.006 P = 0.004). PSMA_TV50 is a promising PSMA PET biomarker that is reproducible and easily quantified by the proposed semiautomated software. Moreover, PSMA_TV50 is a significant predictor of overall survival in patients with advanced prostate cancer who receive ¹⁷⁷Lu-PSMA-617 therapy.