This paper presents the oil quality evaluation system and establishes the two-stage fusion model based on multi-sensor information fusion technology. It also develops the oil quality evaluation model based on neural network model. With the advantages of multi-source information technology, the model implements comprehensive evaluation for oil quality, and provides a set of neural network training process and its results which achieve the oil quality evaluation based on information fusion. The case study shows that the prediction results for four kinds of oil samples by evaluation model based on multi-source fusion are consistent with the actual results. The comparison between operation test trend predictions and actual tests also shows the correctness of the oil quality evaluation model. The proposed multi-information fusion technology for oil quality evaluation system improves the evaluation accuracy and reduces dependence on technical personnel’s analysis experience, which is of great importance for improving the technical management level and the awareness of oil lubrication properties.