Reliability of products has long been considered as an important quality characteristic. Traditional methods of product reliability assessment are based on lifetime data. With products being much more reliable and the growing need for developing new products within shorter period and at lower cost, we can hardly get enough lifetime data in many cases. Performance degradation data can also be used for reliability assessment. Recently, they are found to be useful in some cases where they are easier to collect. But when performance degradation data are also limited and some lifetime data are available, it is preferred to utilize both information sources. This paper deals with the problem of reliability assessment combining both performance degradation data and lifetime data. It is assumed that two samples from the same product are tested differently. Degradation data are collected from one sample and lifetime data from the other. First, the performance degradation model is established, using either statistical methods or methods from physics of failure. Then lifetime of the product, which is defined as the first time when the performance crosses the known failure threshold, is calculated. The MLE method is used for parameter estimation where the maximum likelihood function is multiplication of the one from degradation data and the one from lifetime data. To illustrate the proposed method, an example of the metallized film capacitor, which is used in inertial confinement fusion (ICF) facility, is given. We model the performance degradation data of metallized film capacitor with Wiener process with drift. The failure of the capacitor is defined as the first time when its capacitance drops below a threshold. The lifetime distribution is deduced and the parameters are estimated from the joint maximum likelihood function. A comparison is conducted between the assessment results of degradation data only and those of combination of degradation data and lifetime data. In conclusion we propose that both degradation information and lifetime information should be used when neither of them is sufficient enough for reliability assessment. Some directions for future work are also discussed.