Based on the principle that vancomycin therapy requires sustained therapeutic concentrations while avoiding high peaks, some authors reported that optimal vancomycin levels could be ensured by measuring trough levels alone (Cmin), The aim of this work, was to assess the performance of a one-compartment Bayesian forecasting method for estimating vancomycin 2 hours after Infusion (C2h) and mean vancomycin concentration in steady state (Cavgss) on the basis of a single trough sample (Cmin), in different conditions (steady slate, patient renal function, and age), and according to clinical significance. Vancomycin serum concentrations (n = 108) were analyzed by fluorescence polarization immunoassay, from 79 adult patients. The predictive performance of the Bayesian method was determined by calculating the mean prediction error (ME), the mean absolute error (MAE) and the root squared prediction error (RMSE). A linear regression analysis was carried out between estimated and observed concentrations. The predicted C2h were not significantly different from the observed, and the least biased (ME = -1.08) and most precise (MAE = 3.81) predictions were from patients with normal renal function and steady state conditions. In this population, the concordance in dosage recommendations viith the data pair results was 75% of patients. The best correlation between observed and predicted concentrations was found for Cavgss (r = 0.94;p < 0.00005). Predictions of the Cavgss were more precise (ME = -0.54) and accurate (MAE = 1.74) than the C2h predictions. Vancomycin can be monitored by determining one level in steady state for most patients with normal renal function.