We predict microscopic pK a values using a Gaussian process model trained on 2,443 mono-and diprotic molecules (2,700 data points). Physical and chemical features are calculated for the protonated and deprotonated form of the molecule using OpenEye toolkits (Section 2.2). Macroscopic pK a s are then analytically calculated from a combination of microscopic transitions (Section 2.4). We used our model to predict microscopic (type I) and macroscopic (type III) pK a s for 24 drug like molecules in the SAMPL6 blind challenge . The SAMPL6 submission IDs assigned to our predictions where 6tvf8 (type I) and hytjn (type III). While DLM is a coorganizer of the challenge, none of the authors had any access to the experimental data nor any knowledge of details of the measurements until experimental values and details were publicly released to all participants. The SAMPL6 organizers also asked for optional microstate populations as a function of pH (type II). However, we elected not to participate in that portion of the challenge.