Objective: The aim of this study was to develop a simple predictor model to diagnose malignancy by using ultrasound features of thyroid nodules and the association with cytopathological diagnosis obtained by fine needle aspiration. Materials and Methods: The likelihood of malignancy from ultrasound features was assessed in thyroid nodules obtained by fine-needle aspiration biopsy (FNAB) according to cytopathological findings reported using Bethesda System. A score was developed depending on the presence of each ultrasound feature evaluated. Results: 429 nodules were assessed, 103 (24%) were malignant. The following ultrasound features were associated with malignancy, according to the logistic regression analysis and were assigned a score of 0, +1, +2 depending on the presence or absence of each one: hypoechogenicity, solid appearance, irregular margins, microcalcifications, absence of a halo, diameter of ≥10 mm and intranodular vascular flow. The area under the curve of the proposed model was 0.900, demonstrating its predictive capacity. 4 risk categories were stablished based on the score obtained. Malignant nodules scored higher than the benign nodules (7.24 ± 1.87 vs. 3.74 ± 1.83). Conclusions: The proposed predictive model demonstrated to be useful and easy to apply when stratifying thyroid nodule risk of malignancy using presented US features and applying the proposed risk categories to increase the accuracy at selecting nodules that need to be studied with FNA.