The advancement of medical diagnosis and prognosis is mostly driven by thyroid disorders, which are a complex concept in medical research. One of the major organs in our body is the thyroid gland. The release of thyroid hormones is in charge of controlling metabolism. The two most common thyroid conditions that cause thyroid hormones to be produced for the regulation of body metabolism are hyperthyroidism and hypothyroidism. In order to research and classify thyroid illness using data from hospital databases, machine learning is essential for disease prediction. To tackle dynamic learning problems like medical diagnosis and prediction tasks, a good knowledge base must be assured, constructed, and used as a hybrid model. The identification and inhibition of the thyroid are accomplished using fundamental machine learning techniques. The SVM is used to estimate the likelihood of a thyroid patient with reasonable accuracy. Our system must make recommendations if the patient is at risk for thyroid disease, including home remedies, safety measures, medicine, etc.