Elasticsearch 7.6 introduces classification-based supervised learning, enabling users to predict categories or preferences in datasets, such as movie genres or personal movie preferences. The blog post describes using this feature to build a model that predicts whether a user will like a movie based on its characteristics, using data from the Korean Film Council. The process involves creating a deployment in Elasticsearch, ingesting movie data, and using Logstash for configuration. Users can create a classification model in Kibana to analyze and predict movie preferences, with results accessed through Elasticsearch's inference capabilities. The author shares a personal experience of using the model to choose movies during the COVID-19 lockdown and encourages others to explore classification for various applications, such as predicting loan risks or detecting defects. Configuration and data files used in the demonstration are available in the author's GitHub repository.