Purpose: To study the possibilities of sonoelastography (SEG) in the diagnosis of thyroid tumors. Materials and methods: in 123 patients (27 with papillary thyroid cancer, 45 with thyroid adenomas, and 51 with colloid goiter), different versions of SEG were used at the preoperative stage: compression sonoelastography (CEG) and point shear wave elastography (ARFI). Together with the staining assessment, quantitative parameters were determined: the speed of the transverse wave (M), and the Young’s modulus (E). When using point elastography of the shear wave, the velocity of the transverse wave in m/s was measured. Results: Normal thyroid tissue with CEG had slightly inhomogeneous, uneven fine-grained symmetrical staining with red-yellow tones. With nodular goiter, the staining zones of different colors and intensities were determined, depending on the’ stiffness ‘ of the tissue in the node. Two-color (51.3%) and three-color (33.3%) staining prevailed in the CEG of colloid nodules. The ARFI in thyroid nodules was 3.11 ± 0.75 m/s, and the Young’s modulus was 19.37 8.4 kPa. The thyroid adenomas had different color characteristics and greater variety. Two-color staining occurred in 26.3% of observations, and four-color staining occurred in 47.2%. It was mostly green (58.2%). For ARFI in these tumors presented the cross-wave velocity was 3.96 ± 0.75 m/s, and the Young’s modulus was 35.3 ± 7.4 kp. In most cases, purple-blue-blue staining (76.4%) was detected in the verified RSC. Four-color (26.3%) and five-color (35.2%) coloring prevailed, with a predominance of cold-tone patterns. The ARFI for thyroid cancer was 4.77 ± 0.84 m/s, and the Young’s modulus was 61.22 11.3 kPa. The predictive ability of SEG in the differential diagnosis of thyroid tumors was evaluated using ROC analysis. The model took into account qualitative variables that affect the result. The index AUC = 0.811 (95% CI = 0.765–0.833), indicates that the compression sonoelastography is a test with good quality, but has limits on specificity, which is important in the diagnosis of thyroid cancer. When evaluating ARFI using ROC analysis, it was found that AUC = 0.822 (95% CI = 0.787–0.853). The sensitivity of ARVI was higher than that of KG (87.8%), and the specificity was equal (80.5%). The results obtained were better than the CEG indicators, but the differences were not reliable (P > 0.05). It is difficult to assess microcarcinoma and follicular thyroid cancer, in which both ARFI have low sensitivity and specificity. This reduces the diagnostic effectiveness of the test.