---
title: "Get Predictive Model Measures"
slug: "get-predictive-model-measures"
updated: 2025-08-05T18:26:00Z
published: 2025-08-05T18:26:00Z
canonical: "documentation.decisions.com/get-predictive-model-measures"
---

> ## Documentation Index
> Fetch the complete documentation index at: https://documentation.decisions.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Get Predictive Model Measures

| Step Details |
| --- |
| **Introduced in Version** | Process Mining 3.2 |
| **Last Modified in Version** | Process Mining 3.2 |
| **Location** | Process Mining > Predictions |

The **Get Predictive Model Measures** step in the Decisions Flow toolbox enables users to retrieve a predictive model's performance metrics from a Decisions instance. This provides an alternative to manually checking results in the Process Mining > Prediction > Prediction Center dashboard.

When a Predictive Model ID is provided as input, the step returns a structured set of evaluation metrics describing the model's test data performance. These metrics are critical for assessing the model's ability to predict outcomes and comparing different models or configurations.

---

## Properties

#### Inputs

| Property | Description | Data Type |
| --- | --- | --- |
| Predictive Model ID | The ID of the model available in the Process Mining instance. | Int64 |

#### Outputs

| Property | Description | Data Type |
| --- | --- | --- |
| GetPredictiveModelMeasures_Output | A set of model evaluation metrics: - Accuracy: Proportion of total predictions that are correct. - Precision: Proportion of positive identifications that were actually correct. - Recall: Proportion of actual positives correctly identified. - F-Score: Harmonic mean of precision and recall. - AUC: Area under the ROC curve. - True Positive: Number of correctly predicted positive cases. - True Negative: Number of correctly predicted negative cases. - False Positive: Number of negative cases incorrectly predicted as positive. - False Negative: Number of positive cases incorrectly predicted as negative. | -- |

---

## Example

This example illustrates how to obtain and use the prediction model ID in the Decisions workflow to get the model's evaluation metrics:

1. Log in to the Process Mining dashboard.
2. Navigate to Prediction > Prediction Center dashboard to obtain the model ID. Also, check the status, which currently indicates that the model is Ready. ![](https://cdn.document360.io/6ef8bcc1-6489-4486-9ad1-83acff7e5df0/Images/Documentation/image-1744985266224.png)
3. Log in to the Decisions instance and create a [Flow](https://documentation.decisions.com/docs/create-flows).
4. Drag and drop the **Get Predictive Model Measures** Step from **Toolbox > All Steps > Process Mining > Prediction**.
5. Select the **Get Predictive Model Measures** Step and open the Properties on the top right corner.
6. Enter the model ID obtained from the Process Mining > Prediction > Prediction Center dashboard in the **Predictive Model ID** input field.![](https://cdn.document360.io/6ef8bcc1-6489-4486-9ad1-83acff7e5df0/Images/Documentation/image-1745008491653.png)
7. Click on Debug Flow to test the Step and see the model's evaluation metrics.![](https://cdn.document360.io/6ef8bcc1-6489-4486-9ad1-83acff7e5df0/Images/Documentation/image-1745008539923.png)