**Abstract:** This paper introduces a fully automated system, "NeuroGaze," for the non-invasive, longitudinal assessment of neurological disorder progression, specifically focusing on early-stage Parkinson's Disease (PD) and Alzheimer's Disease (AD). Leveraging advancements in eye-tracking technology, machine learning, and statistical analysis, NeuroGaze dynamically analyzes subtle shifts in gaze patterns to predict disease trajectory with enhanced accuracy compared to traditional clinical assessments. The system integrates dynamic gaze pattern analysis with established clinical scales, providing a quantitative and objective measure of neurological decline usable by researchers and clinicians alike.