This study introduces a simple and computationally efficient protocol for estimating the values of aqueous \(\text{p}K_a\) in three major classes of functional groups: organic acids, alcohols, and amines. Although direct density functional theory calculations yielded notable discrepancies from experimental values, the application of class-specific linear calibration significantly improved predictive accuracy. The correlation coefficients increased from 0.67 (uncalibrated) to 0.98 (calibrated), with mean absolute errors of 0.51, 0.69 and 0.37 \(\text{p}K_a\) units for acids, alcohols, and amines, respectively. The observed class-dependent linear trends validate the chemical consistency of the approach, even in the presence of structural diversity. Correlation analysis showed that predictive errors are largely uncorrelated with standard molecular descriptors, indicating that model performance is predominantly governed by the functional group of the ionizable proton. By avoiding subclass distinctions and relying solely on functional group identity, the method maintains simplicity and broad applicability without sacrificing accuracy. Most predictions fall within \(\pm 0.75\) \(\text{p}K_a\) units, supporting the robustness of the protocol. The approach offers a practical framework for systematic estimation of aqueous \(\text{p}K_a\) , which is a compelling option for routine prediction of aqueous \(\text{p}K_a\) in various chemical contexts.
