---
schema_version: "1"
id: 0345329936ebd018182028f3c5f4b1248a33af548b14b21b949cea2ed710385f
title: Monitor Major Incident Prediction Card
collection: admin
version: current
locale: en-us
portal_url: https://docs.salesforce.com/admin/current/en-us/service/264-0-0/it_srvcs_use_majrincdntcard.md
canonical_url: https://help.salesforce.com/s/articleView?id=service.it_srvcs_use_majrincdntcard.htm&release=264.0.0&type=5
source_site: help.salesforce.com
content_type: documentation
content_hash: c0647cea54f1b62c36f338cf45a3c2da0c039328ead38881ed6c960b818cc251
description: Forecast whether an incident is likely to escalate to a major incident by using machine learning to analyze real-time data and historical patterns. Use the resulting risk scores to initiate response protocols early and reduce business impact.
products:
  - Service Cloud
  - Agentforce IT Service
release: "264"
---
# Monitor Major Incident Prediction Card

Forecast whether an incident is likely to escalate to a major incident by using machine learning to analyze real-time data and historical patterns. Use the resulting risk scores to initiate response protocols early and reduce business impact.

### 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><tr class=""><td class="slds-cell-wrap" style="vertical-align:top;">Available in: <strong>Enterprise</strong>, and <strong>Unlimited</strong> Editions with Einstein for IT Services add-on, and AI Accelerator for IT Services add-on.</td></tr></tbody></table>

1. From the App Launcher, find and select **Incidents**.
2. From the Incidents page, open a record.
3. In an incident record, navigate to the Major Incident Score card in the side panel.
    
    Major Incident Score card displays the probability that the incident will escalate into a major incident.
4. Review the predicted probability to assess the risk level, where a score of 0.08 indicates a very low risk and a score of 98.28 indicates a high risk of escalation.
5. In the Top Predictors list, identify the factors influencing the score.
6. Use the feedback icons to help refine the machine learning model:
    
    - Select the **Thumbs Up** icon if the prediction is accurate.
    - Select the **Thumbs Down** icon if the prediction is incorrect.

**Example:**

![Example](https://sf-zdocs-cdn-prod.zoominsoftware.com/tdta-service-it_service-264-0-0-production-enus/0a574a10-4c7a-4681-aacf-0767f8beaad4/images/icon_example.png)

Example

John, an IT Analyst at Cumulus Bank, triages support ticket influxes following firmware updates. When warehouse operators can't log into handheld scanners, an incident record is created with these details.

- Incident Number: INC-00003879
- Subject: Scanner Authentication Failures - Southeast Hub
- Category: Hardware/Authentication

John opens the record and sees the Major Incident Prediction card with a score of 98.77. This score indicates a near-certainty that the incident will likely escalate into a business-critical event.

John reviews the top predictors list, powered by machine learning, to identify the risk. Predictive AI identifies that the volume of high-priority tickets linked to this issue is the primary driver for the high score. Additionally, historical patterns show that authentication failures with local servers lead to significant shipping disruptions.

To maintain service reliability, John triggers the major incident response protocol. Using data analysis from the major incident score, John ensures engineering and communications teams prioritize the issue before the shipping disruptions occur. The team transitions to a proactive response and reduces the business impact.