A jointly condition-based preventive maintenance and spare parts provisioning policy is discussed for equipment maintenance. Based on analysis of all possible transitions of the joint state of equipment and its spare parts inventory, the explicit expression of stationary joint probability density function is derived and its numerical solution is deduced. On the basis of the joint probability density function, the maintenance probabilities of the equipment with the influence of spare parts inventory and the ordering and holding probabilities of its spare parts are derived. Then the expected long-run cost rate model is formulated for the joint policy using the renewal process, taking into account the costs incurred for performing maintenance and managing the spare parts inventory. A numerical experiment is carried out to identify the optimal values for the parameters of the policy, including the inspection interval, the ordering threshold, and the preventive maintenance threshold. The experiment results verify that the derivation of the joint probability density function is correct and the established model is effective. The results of the sensitivity analysis show that a trade-off exists between the maintenance related costs and the inventory related costs, and joint optimization of preventive maintenance and spare parts provisioning policy can ensure a global optimal policy. A practical case is provided to verify the effectiveness of the proposed method.