diff --git a/fe/fe-core/src/main/java/org/apache/doris/nereids/stats/FilterEstimation.java b/fe/fe-core/src/main/java/org/apache/doris/nereids/stats/FilterEstimation.java
index 915a885a36ad870..70a05f018d8e32e 100644
--- a/fe/fe-core/src/main/java/org/apache/doris/nereids/stats/FilterEstimation.java
+++ b/fe/fe-core/src/main/java/org/apache/doris/nereids/stats/FilterEstimation.java
@@ -68,6 +68,7 @@
  */
 public class FilterEstimation extends ExpressionVisitor<Statistics, EstimationContext> {
     public static final double DEFAULT_INEQUALITY_COEFFICIENT = 0.5;
+    public static final double RANGE_SELECTIVITY_THRESHOULD = 0.01;
     public static final double DEFAULT_IN_COEFFICIENT = 1.0 / 3.0;
 
     public static final double DEFAULT_HAVING_COEFFICIENT = 0.01;
@@ -597,6 +598,8 @@ private Statistics estimateBinaryComparisonFilter(Expression leftExpr, DataType
             double sel = leftRange.overlapPercentWith(rightRange);
             if (!(dataType instanceof RangeScalable) && (sel != 0.0 && sel != 1.0)) {
                 sel = DEFAULT_INEQUALITY_COEFFICIENT;
+            } else if (sel < RANGE_SELECTIVITY_THRESHOULD) {
+                sel = RANGE_SELECTIVITY_THRESHOULD;
             }
             sel = getNotNullSelectivity(leftStats, sel);
             updatedStatistics = context.statistics.withSel(sel);
diff --git a/fe/fe-core/src/test/java/org/apache/doris/nereids/stats/FilterEstimationTest.java b/fe/fe-core/src/test/java/org/apache/doris/nereids/stats/FilterEstimationTest.java
index 981a7e05b919a6e..e5b39e0a7e2c69f 100644
--- a/fe/fe-core/src/test/java/org/apache/doris/nereids/stats/FilterEstimationTest.java
+++ b/fe/fe-core/src/test/java/org/apache/doris/nereids/stats/FilterEstimationTest.java
@@ -1301,7 +1301,9 @@ public void testLargeRange() {
             .setCount(row)
             .setNdv(10000)
             .setMinExpr(new IntLiteral(0))
+            .setMinValue(0)
             .setMaxExpr(new IntLiteral(tenB))
+            .setMaxValue(tenB)
             .build();
         Statistics stats = new StatisticsBuilder()
             .setRowCount(row)
@@ -1310,6 +1312,6 @@ public void testLargeRange() {
         Expression pred = new LessThan(a, new IntegerLiteral(50000));
         FilterEstimation estimation = new FilterEstimation();
         Statistics out = estimation.estimate(pred, stats);
-        System.out.println(out);
+        Assertions.assertEquals(out.getRowCount(), row * FilterEstimation.RANGE_SELECTIVITY_THRESHOULD);
     }
 }