As the decline of fishery resources and the incense of fishery production costs the research of fishery forecasting technology and models has drawn more and more attention and became one of the emphases of fishery oceanography. Fishery forecasting on time, location and fishery resources are essential to fishery production and management. In this text, the theory and methods of fishing condition forecasting are summarized, including fishery oceanography, data models and prediction models related to this subject. Prediction models based on statistics methods and machine learning and artificial intelligence methods are emphasized, as well as the advantages and drawbacks of each kinds of model. Some research perspectives of fishing condition forecasting models are also proposed, i.e. developing ocean environments forecasting system; conducting systematic fishery resources survey of long standing and the standardization and normalization of fishery data acquisition and processing; reducing the uncertainty of prediction models with stochastic simulation methods and improving the prediction accuracy.