In recent times, the prevalence of sleep disorders has increased rapidly, posing serious risks to patient health. Therefore, early detection through an effective method is of utmost importance. Sleep Health and Lifestyle Dataset on Kaggle enables the investigation of Machine Learning techniques to determine sleep states and disorders, as well as analyze lifestyle factors, demographics, and sleep patterns. This study seeks to employ some of the most advanced ML algorithms in classification tasks focused on persistent features such as stress level, Body Mass Index (BMI), Quality of Sleep, Sleep duration, and Heart Rate. The goal is to build models that will recognize sleep state transitions and confirm if the subject suffers from certain disorders like insomnia or sleep apnea syndrome.