Answer: Making the trained model available for use in the production environment within the CRM system to provide real-time predictions on customer data.

**Correct Option:** B. Making the trained model available for use in the production environment within the CRM system to provide real-time predictions on customer data: This is correct because model deployment involves integrating a trained machine learning model into a live production environment where it can be used to make predictions on new data. This step is critical as it allows the model to provide real-world value by processing live data and supporting decision-making or automation processes, aligning with the company's need for real-time predictions within their CRM system. **Incorrect Options:** A. Evaluating the model's performance on a separate test dataset to ensure its predictions are accurate before going live: This is incorrect because evaluating model performance involves assessing how well a trained model performs on validation or test data. While this is an important step, it is separate from the deployment process. C. Creating a new machine learning model from scratch to replace the existing one in the CRM system: This is incorrect because creating a new ML model refers to the process of building and training a machine learning model, which comes before deployment. Model deployment is about putting an already trained model into production. D. Preprocessing the customer data within the CRM system to prepare it for analysis by the machine learning model: This is incorrect because data pre-processing involves cleaning, transforming, and preparing raw data for analysis and model training. This step occurs before model training and deployment.

Author: LeetQuiz Editorial Team