Line Replaceable Units (LRUs), which can be quickly replaced at a first-level maintenance facility, are widely deployed on capital-intensive systems in order to maintain high system availability. Failed LRU are repaired after replacement and reused as fully serviceable spare units. Demand for spare LRUs depends on factors such as the time-varying installed base, reliability deterioration or growth over maintenance cycles, procurement leadtime of new LRUs, turn-around leadtime of repaired LRUs, etc. In this article, we propose an integrated framework for both reliability analysis and spares provisioning for LRUs with a time-varying installed base. We assume that each system consists of multiple types of LRUs and associated with each type of LRU is a non-stationary sub-failure process. The failure of a system is triggered by sub-failure processes that are statistically dependent. A hierarchical probability model is developed for the demand forecasting of LRUs. Based on the forecasted demand, the optimum inventory level is found through dynamic programming. An application example is presented. A computer program, called the Integrated Platform for Reliability Analysis and Spare Provision, is available that makes the proposed methods readily applicable.