In the field of EIS, GPs have been previously used to recover the impedance from the distribution of relaxation times and to analyze the quality of the EIS spectrum through the Hilbert or Kramers-Kronig transforms. This article proposes three new applications of GPs to augment EIS experiments. We used GPs to regress, filter, and smooth noisy EIS spectra, and to predict EIS spectra and polarization resistances. Synthetic and real EIS data were used to validate the approach.