Abstract: Fast and accurate prediction of flood damage is the basis for emergency management of flood disasters, and forecasting techniques and methods are the core and key to flood disaster loss prediction. This paper constructs a flood disaster assessment index system from the aspects of disaster risk component and data accessibility, and selects 13 loss assessment input indicators from disaster-causing factors, affected environment, disaster-bearing object and emergency response capability. A prediction method of flood damage loss based on Gaussian process regression model is proposed, which is applied to the prediction of the flood damage loss in Chongqing of affected number of people, crop affected area and direct economic losses. The example shows that the residual square sum of the three loss cases mentioned above is 0.99, 0.1 and 12.67 respectively, and the fitting precision is 99.85%, 99.97% and 96.1% respectively. Compared with the multi-layer perceptron neural network and support vector machine, the Gauss process regression method is more superior.