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In order to realize the forecasting of equipment technical status based on metrological data which with less historical sample data, the GM (1,1) model of grey theory which suitable for less sample data was applied. And a grey neural network model which based on GM (1,1) traditional model optimized by RBF neural network was proposed, which in order to improve the accuracy of GM (1,1) model. The application analysis of equipment metrological data shows that the models all can obtain the reasonable forecasting value, and compared with the GM (1,1) traditional model, the GM (1,1) optimization model has better model accuracy and forecasting effect. The software of equipment metrological forecasting which developed by MATLAB, which realized the visualization operation of equipment metrological forecasting and comparison which in GM (1,1) traditional and optimization model, provides a reference technical scheme for equipment metrological support.