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diff --git a/Diff for: ‎docs/en/stack/ml/anomaly-detection/forecasting.asciidoc
+1-1 b/Diff for: ‎docs/en/stack/ml/anomaly-detection/forecasting.asciidoc
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diff --git a/Diff for: ‎docs/en/stack/ml/anomaly-detection/images/overview-forecast.jpg
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diff --git a/Diff for: ‎docs/en/stack/ml/anomaly-detection/images/ml-gs-job-analysis.jpg renamed to ‎docs/en/stack/ml/anomaly-detection/images/overview-smv.jpg b/Diff for: ‎docs/en/stack/ml/anomaly-detection/images/ml-gs-job-analysis.jpg renamed to ‎docs/en/stack/ml/anomaly-detection/images/overview-smv.jpg
@@ -24,7 +24,7 @@ actual data values, the bounds for the expected values, and the anomalies that
 occur outside these bounds.
 
 [role="screenshot"]
-image::images/ml-gs-job-analysis.jpg["Example screenshot from the Machine Learning Single Metric Viewer in Kibana"]
+image::images/overview-smv.jpg["Example screenshot from the Machine Learning Single Metric Viewer in Kibana"]
 
 //For a more detailed walk-through of {ml-features}, see
 //<<ml-getting-started>>.
@@ -19,7 +19,7 @@ that you created at different times. You can create a forecast by using the
 example:
 
 [role="screenshot"]
-image::images/ml-gs-forecast.jpg["Example screenshot from the Machine Learning Single Metric Viewer in Kibana"]
+image::images/overview-forecast.jpg["Example screenshot from the Machine Learning Single Metric Viewer in Kibana"]
 
 The yellow line in the chart represents the predicted data values. The
 shaded yellow area represents the bounds for the predicted values, which also