Type 2 diabetes mellitus (T2DM) patient outcomes, treatment options, and corresponding healthcare expenses are affected by the presence of different comorbidities. The aim of this work was to develop an algorithm for predicting the risk of hypothyroidism development in patients with T2DM according to a mathematical model obtained by regression analysis, for the timely implementation of appropriate preventive measures among T2DM patients. We analyzed 538 medical records of T2DM patients. It was found the following risk factors influencing the occurrence of hypothyroidism in patients with T2DM: hemoglobin, total cholesterol, non-HDL-cholesterol, glycated hemoglobin, and thyroid stimulating hormone levels. Prognostic model of the risk of hypothyroidism development in T2DM patients was built using multiple regression analysis. In order to stratify the risk of hypothyroidism development in T2DM patients, the following criteria were proposed: no risk at RC HT ≤ 5.0; low risk at 5.1≤ RC HT≤14,9; high risk at RC HT ≥15.0; where RC HT — risk coefficient for the hypothyroidism development in T2DM patients. Therefore, the developed algorithm and mathematical model for predicting the development of hypothyroidism in T2DM patients are highly informative and allow to determine in advance the contingent of patients with a high probability of hypothyroidism risk based on routine laboratory data.