One of the main objectives of this study was to assess the extent of the most widely used formalisms in the literature for reproducing experimental pH-dependent distribution coefficients in small molecules. To achive this task, we built a database which consists of experimental pKa, logPN, logP I app , and logD7.4 values reported by Avdeef. In addition, we employed experimental The logDpH was calculated using Eq. 1 and Eq. 2 for each molecule at their respective pH values. Figure shows the overall performance of each model by comparing the modeled values with their respective experimental logDpH values. As expected, most of the molecules whose logDpH values were measured under different pH conditions to 7.4, present the largest deviation using Eq. 1 (see Figure , red marks), with highly underestimated predictions. As a consequence, Eq. 1 poorly predicts logDpH values at extreme pH values. On the other hand, the predicted values using the Eq. 2 are significantly better (see Figure ), reducing the RMSE by 0.48 logD units, which represents an improvement of 55% in accuracy. Table shows the reduction of RMSE in logD units of each molecule type using Eq.2 instead of Eq.1. It is observed that our dataset shows a significant improvement (ca. 54 %) in its performance when its distribution coefficient is modeled with logDEq.2 (see Figure ). Basic molecules showed the greatest improvement, amounting to 66 %, whereas the acid ones 44 %.