An abnormality diagnosis system diagnosing abnormality in a plant, comprising: an abnormality diagnosis control unit configured to predict a development of an instrument parameter through extrapolation of the instrument parameter measured in the plant and determined as there being an abnormality prediction, and generate an abnormality symptom motion pattern corresponding to a pattern of a behavior of the instrument parameter after prediction; and a data storage unit configured to store a plurality of abnormality model patterns (PA, PB) corresponding to patterns of a behavior of the instrument parameter corresponding to abnormality causes of the plant, wherein the abnormality diagnosis control unit is configured to determine whether or not the generated abnormality symptom motion pattern matches the plurality of abnormality model patterns stored in the data storage unit, and specify an abnormality cause of an abnormality model pattern determined as matching the abnormality symptom motion pattern, as abnormality cause of the abnormality symptom motion pattern, wherein the abnormality symptom motion pattern of the instrument parameter is correlated with both a plurality of the abnormality causes and occurrence probabilities of the respective abnormality causes, the data storage unit stores a statistical model which is built on the basis of the abnormality cause correlated with the abnormality symptom motion pattern and an occurrence probability of the abnormality cause, wherein when there is a plurality of abnormality causes corresponding to the abnormality model pattern, the abnormality diagnosis control unit is configured to specify an occurrence probability corresponding to each abnormality cause along with the plurality of abnormality causes by using the statistical model; wherein, when there is a plurality of the abnormality symptom motion patterns of the instrument parameter, the abnormality diagnosis control unit is configured to specify the abnormality cause and the occurrence probability of the abnormality cause on the basis of the plurality of abnormality symptom motion patterns by using the statistical model, and wherein the statistical model is a Bayesian network. an abnormality diagnosis control unit configured to predict a development of an instrument parameter through extrapolation of the instrument parameter measured in the plant and determined as there being an abnormality prediction, and generate an abnormality symptom motion pattern corresponding to a pattern of a behavior of the instrument parameter after prediction; and a data storage unit configured to store a plurality of abnormality model patterns (PA, PB) corresponding to patterns of a behavior of the instrument parameter corresponding to abnormality causes of the plant, wherein the abnormality diagnosis control unit is configured to determine whether or not the generated abnormality symptom motion pattern matches the plurality of abnormality model patterns stored in the data storage unit, and specify an abnormality cause of an abnormality model pattern determined as matching the abnormality symptom motion pattern, as abnormality cause of the abnormality symptom motion pattern, wherein the abnormality symptom motion pattern of the instrument parameter is correlated with both a plurality of the abnormality causes and occurrence probabilities of the respective abnormality causes, the data storage unit stores a statistical model which is built on the basis of the abnormality cause correlated with the abnormality symptom motion pattern and an occurrence probability of the abnormality cause, wherein when there is a plurality of abnormality causes corresponding to the abnormality model pattern, the abnormality diagnosis control unit is configured to specify an occurrence probability corresponding to each abnormality cause along with the plurality of abnormality causes by using the statistical model; wherein, when there is a plurality of the abnormality symptom motion patterns of the instrument parameter, the abnormality diagnosis control unit is configured to specify the abnormality cause and the occurrence probability of the abnormality cause on the basis of the plurality of abnormality symptom motion patterns by using the statistical model, and wherein the statistical model is a Bayesian network.