Vital:RPM is a mobile application developed for my final-year research project - Based around the telehealth domain, the application supports remote monitoring of patient vital signs (blood pressure, temperature, blood oxygen saturation, respiratory rate & heart rate) allowing the user to add measurement data and receive current health status assessments and also predicted status assessments based on prior data. This status assessment could then be utilized to alert healthcare providers to ensure efficient care. The system was developed utilizing the Flutter framework as the frontend, Firebase, Flask, Heroku, and Google Cloud Storage were also used to host and store the machine learning models. The application makes use of several machine learning models where the system utilizes a hybrid machine learning model & a vital sign forecasting model to assist with the final status assessments. The models were trained using the MIMIC IV Dataset provided by MIT ensuring best practices & ethics.