Scientific prediction is necessary to study economic phenomena and make economic decisions. Moreover, regional logistics demand forecast in regional logistics planning and decision-making is based on the premise of scientific and rational logistics demand forecasting method, which is particularly important. This article combines the Gray Prediction Method GM (1, 1) and Markov Prediction Method and puts forward the Gray-Markov Method. Firstly, a GM (1, 1) model chain is built. Secondly, on the basis of the GM (1, 1), Markov chain is applied to achieve state transition probability matrix. Lastly, through the division of the system state, analysis and calculation of the deviation between the sample value and the model value, predicted values are expressed in the form of probability and interval. The improved gray - Markov chain forecasting method is used in Guangxi logistics demand forecast subsequently. It shows gray - Markov chain forecasting approach is more accurate and reliable for policy makers.
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