The study of low-resourced East Slavic lects is becoming increasingly relevant as they face the prospect of extinction under the pressure of standard Russian while being treated by academia as an inferior part of this lect. The Khislavichi lect, spoken in a settlement on the border of Russia and Belarus, is a perfect example of such an attitude.We take an alternative approach and study East Slavic lects (such as Khislavichi) as separate systems. The proposed method includes the development of a tagged corpus through morphological tagging with the models trained on the bigger lects. Morphological tagging results may be used to place these lects among the bigger ones, such as standard Belarusian or standard Russian. The implemented morphological taggers of standard Russian and standard Belarusian demonstrate an accuracy higher than the accuracy of multilingual models by 3 to 15%. The study suggests possible ways to adapt these taggers to the Khislavichi dataset, such as tagset unification and transcription closer to the actual sound rather than the standard lect pronunciation. Automatic classification supports the hypothesis that Khislavichi is a border East Slavic lect that historically was Belarusian but got russified: the algorithm places it either slightly closer to Russian or to Belarusian.