An administration plan for vancomycin (VCM) in bedridden elderly patients has not been established. This retrospective study aimed to evaluate the prediction accuracy of the area under the concentration-time curve (AUC) of VCM by the Bayesian approach using creatinine-based equations of estimated kidney function in such patients. Kidney function was estimated using the Japanese equation of estimated glomerular filtration rate (eGFR) and the Cockcroft-Gault equation of estimated creatinine clearance (eCCr). eCCr (serum creatinine (SCr) 0.2) was calculated by substituting the SCr level 0.2 mg/dL into the Cockcroft-Gault equation. For eGFR/0.789, eGFR, eCCr, and eCCr (SCr 0.2), the AUC values were calculated by the Bayesian approach using the therapeutic drug monitoring (TDM) software, BMs-Pod (ver 8.06) and denoted as AUC eGFR/0.789 , AUC eGFR , AUC eCCr , and AUC eCCr (SCr 0.2) respectively. The reference AUC (AUC REF ) was calculated by applying VCM's peak and trough steady-state concentrations to first-order pharmacokinetic equations. The medians (range) of AUC eGFR/0.789 /AUC REF , AUC eGFR /AUC REF , AUC eCCr /AUC REF , and AUC eCCr (SCr 0.2) /AUC REF were 0.88 (0.74-0.93), 0.90 (0.79-1.04), 0.92 (0.81-1.07), and 1.00 (0.88-1.11), respectively. Moreover, the percentage of patients within 10% of the AUC REF , defined as |Bayesian-estimated AUC AUC REF | < AUC REF 0.1, was the highest (86%) in AUC eCCr (SCr 0.2) . These results suggest that the Bayesian approach using eCCr (SCr 0.2) has the highest prediction accuracy for the AUC REF in bedridden elderly patients. Although further studies are required with more accurate determination methods of the CCr and AUC, our findings highlight the potential of eCCr (SCr 0.2) for estimating VCM's AUC by the Bayesian approach in such patients.