In this paper, we present a forecasting method for the view of Mt. Fuji as an application of Earth observation data (EOD) obtained by satellites. We defined the Mt. Fuji viewing index (FVI) that characterises how well the mountain looks on a given day, based on photo data produced by a fixed-point observation. A long-term predictor of FVI, ranging from 0 to 30 days, was constructed through support vector machine regression on climate and earth observation data. It was found that the aerosol mass concentration (AMC) improves prediction performance, and such performance is particularly significant in the long-term range.