KEYWORDSIn this work, principal component regression and partial least squares regression were used for the estimation of acid dissociation constants through UV-Vis spectrophotometric measurements, considering five well-known acid-base indicators as well as two herbicides as analytes. In each case, an acid-base titration was carried out. Then, the multivariate calibration model was constructed with a few absorption spectra of the series at extreme pH values, to which values of the dissociation fraction (α) of 1 or 0 were assigned, in the case of HA or A species. After that, the prediction step consisted in the estimation of α for the rest of the series. Then, distribution diagrams were built up with α vs pH, to find α = 0.5 where pH = pKa. The results were compared with those obtained through multivariate curve resolutionalternating least squares and program stability quotients from absorbance data (SQUAD), which showed an excellent correspondence. pKa PLS PCR MCR-ALS Spectrophotometry Chemometric strategies