Knee osteoarthritis (OA) develops as a common degenerative joint condition by deteriorating cartilage tissue to produce joint pain that combines with joint stiffness and restricted knee movement range. The disability burden worldwide has maximized due to this health condition which targets elderly patients primarily. The predictive model employs deep learning technology to construct a forecasting system by processing different patient datasets that combine demographic information with past medical records as well as medical imaging scans for knee osteoarthritis advancement prediction. The ResNet deep learning networks enable the model to detect early markers of OA thus enabling doctors to identify suitable treatment options at an optimal time. The proposed method demonstrates great potential for knee osteoarthritis management because it provides precise noninvasive early diagnosis and prognosis capabilities through an easily scalable platform.