> For the complete documentation index, see [llms.txt](https://docs.datasaur.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.datasaur.ai/advanced/extensions/predictive-labeling.md).
# Predictive Labeling
Predictive labeling generates labels based on your existing labeled data.
## Overview
**Predictive labeling** uses machine learning to generate labels based on a subset of manually labeled data. It helps reduce manual labeling effort and improves consistency, especially for large datasets.
## Use case
This example uses **Predictive labeling** for spam message detection.
1. Create a [row labeling](/data-studio-projects/creating-a-project.md) project.
2. Click the gear icon from the extension panel on the right to open the **Manage extensions** dialog, then enable the **Predictive labeling** extension.
3. Label at least five items for each answer option. For example, if you have two answer options (`True` and `False`), label at least five items as `True` and five items as `False`.
4. Select the input columns as context for the prediction and select the target field where predicted labels will be added. Then click **Save configuration**.
5. Review the predicted labels and choose **Accept** or **Reject**.
{% hint style="info" %}
For further details, please visit [Assisted Labeling - Predictive Labeling](/assisted-labeling/predictive-labeling.md).
{% endhint %}
