The system, product and equipment often experiences a long period of non-operating period(dormancy or storage) prior to use in its intended function. During non-operating storage period, these systems can be affected by many factors such as temperature, humidity, on-off cycling stress, degradation process and so on. The reliability prediction on these dormancy or storage states is very crucial to their life cycle reliability management for the system improvement and mission reliability achievement. Many theories and methods are proposed for non-operating storage reliability prediction in the literature, but few are applied into practice and old outdated inaccurate MIL-HDBK 217 style-based methods are used by many field engineer in the usual manner. In this paper, storage reliability assessment methods and models based-on failure rate data-book under non-operating state with a long storage time are reviewed and described. Also, if there are available actual field data, this paper presents a reliability assessment framework approach using logistic regression model during non-operating period. By utilizing this framework, end-user is able to develop data-based ad-hoc prediction models more easily and expected to save cost of reliability analysis during the life-cycle of reliability management.