Rapid advances in technology and intense global competition have put high pressure on manufacturers to produce high-quality products. The high-reliability design of products causes problems of collecting complete life information from life tests. To design an efficient online monitoring tool for high-reliability products is an important part of the lager overall picture on improving the quality of products. An exponentially weighted moving average (EWMA) control chart has been identified as an excellent online monitoring tool for detecting small changes of the process parameter from its target value. Assume that Type I censored data are collected, this article proposes an EWMA control chart based on the conditional median values (CMVs) for Gompertz process to enhance the ability of detecting small changes of the process parameter from its target value and reduce the sensitivity of control chart due to outliers. An algorithm is suggested to determine the multiplier of control limits. An example is used to demonstrate the implementation of the proposed method. Intensive simulations are conducted to evaluate the performance of the proposed control chart in terms of the average run length (ARL). Numerical results show that the proposed control chart is good at detecting medium shift either in decrease or in big increase for Gompertz process.