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First, you need to save your auto-model process. Then you should open that and add a "Store" operator to keep the model itself.
You will then need to look at whatever data-preprocessing occurred as part of the auto-model process (such as replacing missing values, turning nominal to numerical data, etc.). You will also need to create a process to perform that same data ETL on new records.
When you get new records to score, you will then need to run them through the data preprocessing ETL steps, and then you will be able to use the "Apply Model" operator (using the model you stored above) to generate a new prediction.
All of this is covered in the many self-directed exercises on the "RapidMiner: Getting Started" page, or in the RapidMiner & Data Science Foundations training course, if you need more explicit hands-on instruction.
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