---
schema_version: "1"
id: 78b83f84c6d9727016d5fb101f906c2409c16d428df60231ea0ba53cd9f5f022
title: Select a Predictive Model
collection: admin
version: current
locale: en-us
portal_url: https://docs.salesforce.com/admin/current/en-us/ind/264-0-0/ai_accelerator_configure_usecase_model.md
canonical_url: https://help.salesforce.com/s/articleView?id=ind.ai_accelerator_configure_usecase_model.htm&release=264.0.0&type=5
source_site: help.salesforce.com
content_type: documentation
content_hash: 6eaff9106fded192fc446d84689e78aceef5db06231cb42669f3db3a388b973e
description: Select the predictive model that you deployed to get predictions for your use case.
products:
  - Industry Solutions
  - Cross Cloud
release: "264"
---
# Select a Predictive Model

Select the predictive model that you deployed to get predictions for your use case.

### Required Editions

<table class="slds-table slds-table_bordered slds-max-medium-table_stacked slds-m-bottom_small edition"><colgroup><col></colgroup><tbody><tr class=""><td class="slds-cell-wrap" style="vertical-align:top;">Available in: Lightning Experience</td></tr></tbody></table>

<table class="slds-table slds-table_bordered slds-max-medium-table_stacked slds-m-bottom_small permission">
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            <th scope="colgroup" class="slds-cell-wrap" colspan="2" style="text-align:center;vertical-align:top;" id="d2123e54">User Permissions Needed</th>
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            <td data-label="User Permissions Needed" class="slds-cell-wrap" style="vertical-align:top;" headers="d2123e54 ">To select a model:</td>

            <td class="slds-cell-wrap" style="vertical-align:top;" headers="d2123e54 ">Customize Application</td>

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1. From Setup, in the Quick Find box, enter Industries Einstein, and then select **AI Accelerator**.
2. Click **Edit** for your use case, and then go to the Use Case Model section.
3. Click **Add Model**.
    
    A row with a Prediction Platform field and Model field is added.
4. Select the **Prediction Platform**.
    1. Einstein Discovery: Select this option if you want to use Salesforce's Einstein Discovery tool for predictive analytics. By default, this option is selected.
    2. Data Cloud BYOM (Bring Your Own Model): Select this option if you want to integrate a machine learning model built in Amazon SageMaker into your use case.
    3. Einstein on Data Cloud: Select this option if you want to use Salesforce's Einstein capabilities on Data Cloud for your predictive model.
5. Select a machine learning model.
    
    You can select multiple machine learning models for a use case.
    
    ![Tip](https://sf-zdocs-cdn-prod.zoominsoftware.com/tdta-ind-ai_accelerator_scoring_framework-264-0-0-production-enus/579cbc22-5fe0-45e4-b0a0-608ab8690ae6/images/icon_tip.png)
    
    Tip If no models are available to select, no unused models exist in your org. Create an Insights & Predictions model, deploy the predictive model, and then retry.
6. If you’ve selected Einstein on Data Cloud and Data Cloud BYOM (Bring Your Own Model), complete these steps:
    1. Enter **Usecase Model Name** to identify the particular use case model. Based on the Usecase Model Name entered, the Usecase Model API Name is auto-filled.
    2. Select **Prediction Mode**. You can select either **Generate in real time with AI Accelerator** or **Already generated**. If you select Generate in real time with AI Accelerator, you can select the Model. If you select Already Generated, you can select a Data Space.
    3. Select a score field that displays the score and any additional variables selected. The options are listed based on the selected model.
    4. To include other fields in the prediction card, click **Add Input Field**. Then, enter the field label and the source field to map.
    5. Select a **Reference Record** field that is associated with the primary key of the record. This allows the model to be queried using this primary key and displays all fields on the card.
    6. To specify the prediction sorting order and set the display order in the scorecard, click **Add Sort Preference**. Then, select the source field and sort order.
    7. Create a template that defines how to display the selected fields on the prediction card. You can add variables such as %%Score%%, which represents the likelihood of asset failure. If you select multiple fields, you can write text that includes these variables, and they will be shown on the prediction card.
7. Save your changes.
    
    ![Note](https://sf-zdocs-cdn-prod.zoominsoftware.com/tdta-ind-ai_accelerator_scoring_framework-264-0-0-production-enus/579cbc22-5fe0-45e4-b0a0-608ab8690ae6/images/icon_note.png)
    
    Note If a model selected for a use case is deleted, the use case becomes invalid.