The present disclosure provides a system and method for predicting college entrance acceptance probability and linking educational content. The method includes the steps of collecting and updating evaluation criteria data including evaluation criteria for each university and department, score data of a university entrance test, and score data of a university entrance mock test from linked external data sources, the user's test score from the user terminal Step of receiving information, predicting the possibility of passing a specific department of a specific university based on the updated evaluation criteria data and the test result information, which is defined according to the test subject and question type based on the test result information Determining a customer type matching the user from among customer types and determining one or more educational contents to be provided to the user terminal and a recommendation ranking based on a recommendation algorithm according to the preferences of users belonging to the customer type can do. Through the present disclosure, it is possible to implement an entrance examination consulting platform that predicts a reliable passability for a target university and department, and provides areas required for reinforcement learning and customized educational contents to examinees.
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