Ozone plays a crucial role in climate formation, and it shields life on Earth from harmful UV radiation. Ozone in the troposphere is a pollutant and greenhouse gas. Therefore, it is essential to monitor both total and tropospheric ozone columns. Only satellite methods can be used to monitor the global distribution of ozone. Satellite methods that use the measurements of outgoing thermal radiation are the only methods that provide information on ozone not depending on solar illumination. We present the techniques for deriving information on total ozone columns (TOCs) and tropospheric ozone columns (TrOCs) from spectra of outgoing thermal radiation measured by the IKFS-2 instrument aboard the ’Meteor-M’ No. 2 satellite, which are based on the artificial neural network (ANN) approach and the principal component analysis. The data were obtained for the period from 2015 to the end of 2022 from the Meteor-M satellite No. 2. On average, the mean differences between independent and IKFS-2 TOC measurements are less than 2%; the standard deviations of differences are less than 3%. The retrieval results demonstrate that the standard deviations of differences between IKFS-2 TrOC data and independent measurements are within 2-4 DU, which is consistent with the results obtained by using similar instruments.