An information processing device comprising: an information acquisition unit configured to receive an input of image data and non-image data related to a target matter; and a prediction unit configured to predict an aspect related to the matter at a time different from a time when the image data is captured on the basis of the image data and the non-image data input through the information acquisition unit , wherein the prediction unit includes: a first processing unit configured to calculate the first feature amount from the image data, a second processing unit configured to calculate the second feature amount from the non-image data, and a third processing unit configured to perform weighting calculation by a calculation method, which outputs a combination of products of elements of (i) a first feature amount calculated from the image data and (ii) a second feature amount calculated from the non-image data, to calculate a third feature amount in which the first feature amount and the second feature amount are fused and performs the prediction on the basis of the third feature amount; wherein the target matter is a disease state of a subject with mild cognitive impairment, the image data is a medical image obtained by imaging a brain of the subject, the non-image data includes at least one of blood test data, genetic data, or a cognitive ability score of the subject, and age and gender of the subject, and the prediction unit predicts whether the disease state of the subject will be Alzheimer's disease or the mild cognitive impairment after a lapse of a specific period from a time when the medical image is captured. an information acquisition unit configured to receive an input of image data and non-image data related to a target matter; and a prediction unit configured to predict an aspect related to the matter at a time different from a time when the image data is captured on the basis of the image data and the non-image data input through the information acquisition unit , wherein the prediction unit includes: a first processing unit configured to calculate the first feature amount from the image data, a second processing unit configured to calculate the second feature amount from the non-image data, and a third processing unit configured to perform weighting calculation by a calculation method, which outputs a combination of products of elements of (i) a first feature amount calculated from the image data and (ii) a second feature amount calculated from the non-image data, to calculate a third feature amount in which the first feature amount and the second feature amount are fused and performs the prediction on the basis of the third feature amount; a first processing unit configured to calculate the first feature amount from the image data, a second processing unit configured to calculate the second feature amount from the non-image data, and a third processing unit configured to perform weighting calculation by a calculation method, which outputs a combination of products of elements of (i) a first feature amount calculated from the image data and (ii) a second feature amount calculated from the non-image data, to calculate a third feature amount in which the first feature amount and the second feature amount are fused and performs the prediction on the basis of the third feature amount; wherein the target matter is a disease state of a subject with mild cognitive impairment, the image data is a medical image obtained by imaging a brain of the subject, the non-image data includes at least one of blood test data, genetic data, or a cognitive ability score of the subject, and age and gender of the subject, and the prediction unit predicts whether the disease state of the subject will be Alzheimer's disease or the mild cognitive impairment after a lapse of a specific period from a time when the medical image is captured. <EOS>