The design purpose of preventive health exams (PHEs) is to identify early asymptomatic disease and function that may affect health, making the exams a crucial measure in preventative healthcare. However, in practice, before health examinations, the majority of the public lacks practical personal health assessment for planning personal health examinations. This greatly affects the results and effectiveness of PHEs. To address this problem, this study proposes a virtual health examination (VHE) system that predicts examination results prior to health examinations, allowing people to conveniently select relevant test items before deciding to proceed with the actual examinations. The VHE model is designed to facilitate the support of all examination items and various grades or levels of health examination. The model uses cloud computing virtualization technology to rapidly integrate existing exam prediction models or newly developed models and follows a multi-level prediction framework. Therefore, different levels of VHE models can be constructed for each examination item, allowing the system to assemble various grades or levels of VHEs. Additionally, to respond rapidly to the large quantity of enquiries from the public, the system employs a cloud computing architectural design. Specifically, the VHE models deployed within the system are driven by the collaborative operations of two units in the system, vheMap and vheSum, to increase computing efficiency. This allows people to obtain their virtual exam reports quickly.