The mental debris produced by the wear of power-shift steering transmission(PSST), which is uniformly mixed in lubrication oil, leads to the working environment degradation and the PSST failure afterwards. Therefore, it is essential to monitor the PSST degradation degree and formulate the condition-based maintenance(CBM) strategy, which can help improve the reliability and maintainability of the PSST. The oil spectral data contain wear position and wear state information, and its relationship with the PSST life reflects the distribution of the PSST degradation, which makes the oil spectral data-based degradation modeling and maintenance decision become possible. However, the current CBM studies of PSST are implemented by trend analysis of spectral oil data combined with predetermined threshold, without considering the maintenance costs and the equipment availability. In this paper, the CBM decision method of PSST is presented based on spectral oil data. First, considering the relationship between the PSST life and degradation variables and the contribution rate of each degradation variable to PSST degradation, the life model is established based on Weibull proportional hazards regression using the spectral oil data from historical faults. Then, the maintenance decision model of the PSST is further established with the minimum maintenance cost and maximum availability as the maintenance objectives for the training exercise and the execution task, respectively. Compared with the traditional PSST maintenance decision method, the proposed method takes into account the influence of maintenance cost and equipment availability, which provides an objective quantization scheme for CBM decision that can effectively determine the optimal maintenance time of the PSST according to the maintenance objectives. Finally, the effectiveness of the proposed method is verified by a case study using spectral oil datum from historical faults of several Ch series PSST, and the results indicate that the proposed method provides a reasonable formulation of the PSST maintenance strategy. The proposed method also provides a useful reference for other equipment’s maintenance decision.