@@ -880,10 +880,7 @@ async fn parquet_explain_analyze() {
 
     // should contain aggregated stats
     assert_contains!(&formatted, "output_rows=8");
-    assert_contains!(
-        &formatted,
-        "row_groups_pruned_bloom_filter=1 total \u{2192} 1 matched"
-    );
+    assert_not_contains!(&formatted, "row_groups_pruned_bloom_filter");
     assert_contains!(
         &formatted,
         "row_groups_pruned_statistics=1 total \u{2192} 1 matched"
@@ -896,16 +893,14 @@ async fn parquet_explain_analyze() {
     // (file-> row-group -> page)
     let i_file = formatted.find("files_ranges_pruned_statistics").unwrap();
     let i_rowgroup_stat = formatted.find("row_groups_pruned_statistics").unwrap();
-    let i_rowgroup_bloomfilter =
-        formatted.find("row_groups_pruned_bloom_filter").unwrap();
     let i_page_rows = formatted.find("page_index_rows_pruned").unwrap();
     let i_page_pages = formatted.find("page_index_pages_pruned").unwrap();
 
     assert!(
         (i_file < i_rowgroup_stat)
-            && (i_rowgroup_stat < i_rowgroup_bloomfilter)
-            && (i_rowgroup_bloomfilter < i_page_pages && i_page_pages < i_page_rows),
-        "The parquet pruning metrics should be displayed in an order of: file range -> row group statistics -> row group bloom filter -> page index."
+            && (i_rowgroup_stat < i_page_pages)
+            && (i_page_pages < i_page_rows),
+        "The parquet pruning metrics should be displayed in an order of: file range -> row group statistics -> page index."
     );
 }
 
@@ -1179,7 +1174,7 @@ async fn parquet_explain_analyze_verbose() {
         .to_string();
 
     // should contain the raw per file stats (with the label)
-    assert_contains!(&formatted, "row_groups_pruned_bloom_filter{partition=0");
+    assert_not_contains!(&formatted, "row_groups_pruned_bloom_filter");
     assert_contains!(&formatted, "row_groups_pruned_statistics{partition=0");
 }
 
 
@@ -1336,26 +1336,14 @@ impl FiltersPreparedParquetOpen {
                     .row_groups_pruned_statistics
                     .add_matched(row_groups.remaining_row_group_count());
             }
-
-            if !prepared.enable_bloom_filter || row_groups.is_empty() {
-                // Update metrics: bloom filter unavailable, so all row groups are
-                // matched (not pruned)
-                prepared
-                    .file_metrics
-                    .row_groups_pruned_bloom_filter
-                    .add_matched(row_groups.remaining_row_group_count());
-            }
         } else {
             // Update metrics: no predicate, so all row groups are matched (not pruned)
+            // by statistics. Bloom pruning did not run, so its metrics are unchanged.
             let remaining = row_groups.remaining_row_group_count();
             prepared
                 .file_metrics
                 .row_groups_pruned_statistics
                 .add_matched(remaining);
-            prepared
-                .file_metrics
-                .row_groups_pruned_bloom_filter
-                .add_matched(remaining);
         }
 
         Ok(RowGroupsPrunedParquetOpen {
@@ -3413,6 +3401,32 @@ mod test {
             .expect("row_groups_pruned_statistics metric is emitted")
     }
 
+    /// Bloom pruning counters after a scan, as `(pruned, matched)`.
+    ///
+    /// Direct `MetricsSet` lookup, not plan display: idle Bloom metrics are
+    /// omitted from displayed plans even when the counters remain registered.
+    ///
+    /// Opening one file still registers this name more than once:
+    /// `prepare_open_file` creates `ParquetFileMetrics`, and each
+    /// `ParquetFileReaderFactory::create_reader` call (initial reader plus
+    /// Bloom replacement reader) creates another independent set. Sum the
+    /// counters the same way `MetricsSet::sum_by_name` aggregates pruning
+    /// metrics. Only the opener's set is incremented by Bloom pruning; the
+    /// reader copies stay at zero.
+    fn bloom_filter_pruning_metrics(metrics: &ExecutionPlanMetricsSet) -> (usize, usize) {
+        use datafusion_physical_plan::metrics::MetricValue;
+        match metrics
+            .clone_inner()
+            .sum_by_name("row_groups_pruned_bloom_filter")
+        {
+            Some(MetricValue::PruningMetrics {
+                pruning_metrics, ..
+            }) => (pruning_metrics.pruned(), pruning_metrics.matched()),
+            Some(_) => panic!("row_groups_pruned_bloom_filter is not a pruning metric"),
+            None => panic!("row_groups_pruned_bloom_filter metric is registered"),
+        }
+    }
+
     #[tokio::test]
     async fn test_prune_all_null_column_equality_from_file_statistics() {
         // Regression: a column whose file statistics say every value is
@@ -4743,6 +4757,16 @@ mod test {
             // contribute to this metric.
             bloom_bytes.push(counter_metric_value(&metrics, "bytes_scanned"));
             assert_eq!(collect_int32_values(stream).await, vec![1, 1, 1, 1]);
+            let (pruned, matched) = bloom_filter_pruning_metrics(&metrics);
+            assert_eq!(pruned, 0);
+            if stats_pruning {
+                // [1,1,1] is fully matched by statistics and skips Bloom.
+                // [0,1,2] still evaluates Bloom for `a = 1` and cannot prune.
+                assert_eq!(matched, 1);
+            } else {
+                // Statistics pruning is off, so both row groups evaluate Bloom.
+                assert_eq!(matched, 2);
+            }
         }
         assert!(bloom_bytes[1] > 0, "partial row group needs Bloom I/O");
         assert!(
@@ -4781,6 +4805,10 @@ mod test {
         .unwrap();
         assert_eq!(counter_metric_value(&metrics, "bytes_scanned"), 0);
         assert_eq!(collect_int32_values(stream).await, vec![1, 1, 1]);
+        let (pruned, matched) = bloom_filter_pruning_metrics(&metrics);
+        // Bloom reads and evaluation are skipped for an entirely fully matched file.
+        assert_eq!(pruned, 0);
+        assert_eq!(matched, 0);
     }
 
     #[test]
 
@@ -472,7 +472,8 @@ impl RowGroupAccessPlanFilter {
             }
 
             if self.access_plan.is_fully_matched(idx) {
-                metrics.row_groups_pruned_bloom_filter.add_matched(1);
+                // Statistics already proved every row matches. Bloom did not
+                // evaluate this group, so do not record a Bloom outcome.
                 continue;
             }
 
@@ -481,7 +482,6 @@ impl RowGroupAccessPlanFilter {
             // evaluation in that case: it runs once per row group and can be expensive for wide
             // predicates, a cost files written without bloom filters would pay for nothing.
             if stats.is_empty() {
-                metrics.row_groups_pruned_bloom_filter.add_matched(1);
                 continue;
             }
 
@@ -493,7 +493,7 @@ impl RowGroupAccessPlanFilter {
                         "Error evaluating row group predicate on bloom filter: {e}"
                     );
                     metrics.predicate_evaluation_errors.add(1);
-                    false
+                    continue;
                 }
             };
 
@@ -622,9 +622,12 @@ mod tests {
 
     use arrow::datatypes::DataType::Decimal128;
     use arrow::datatypes::{DataType, Field};
-    use datafusion_expr::{cast, col, lit};
-    use datafusion_physical_expr::PhysicalExpr;
+    use datafusion_expr::{Operator, cast, col, lit};
     use datafusion_physical_expr::planner::logical2physical;
+    use datafusion_physical_expr::{
+        PhysicalExpr,
+        expressions::{BinaryExpr, CastExpr, Column as PhysicalColumn, Literal},
+    };
     use datafusion_physical_plan::metrics::ExecutionPlanMetricsSet;
     use datafusion_pruning::PruningPredicateBuilder;
     use parquet::arrow::ArrowSchemaConverter;
@@ -1640,7 +1643,49 @@ mod tests {
         // the row group with a bloom filter is still evaluated and pruned.
         assert_pruned(row_groups, ExpectedPruning::Some(vec![0]));
         assert_eq!(metrics.row_groups_pruned_bloom_filter.pruned(), 1);
-        assert_eq!(metrics.row_groups_pruned_bloom_filter.matched(), 1);
+        assert_eq!(metrics.row_groups_pruned_bloom_filter.matched(), 0);
+    }
+
+    #[test]
+    fn bloom_filter_pruning_error_retains_row_group_without_match() {
+        let schema =
+            Arc::new(Schema::new(vec![Field::new("c1", DataType::Int32, false)]));
+        let cast_expr: Arc<dyn PhysicalExpr> = Arc::new(CastExpr::new(
+            Arc::new(PhysicalColumn::new("c1", 0)),
+            DataType::FixedSizeBinary(4),
+            None,
+        ));
+        let literal: Arc<dyn PhysicalExpr> = Arc::new(Literal::new(
+            ScalarValue::FixedSizeBinary(4, Some(vec![0, 0, 0, 1])),
+        ));
+        let expr = Arc::new(BinaryExpr::new(cast_expr, Operator::Eq, literal));
+        let pruning_predicate = PruningPredicateBuilder::new()
+            .with_file_schema(schema)
+            .try_build(expr)
+            .unwrap();
+
+        // A nonempty map bypasses the no-filter path. Evaluating the predicate
+        // then fails because Arrow cannot cast Int32 statistics to FixedSizeBinary.
+        let mut sbbf = Sbbf::new_with_ndv_fpp(10, 0.01).unwrap();
+        sbbf.insert(&1_i32);
+        let mut bloom_statistics = BloomFilterStatistics::new();
+        bloom_statistics.insert("loaded_filter", sbbf, PhysicalType::INT32, 4);
+        assert!(pruning_predicate.prune(&bloom_statistics).is_err());
+
+        let metrics = parquet_file_metrics();
+        let mut row_groups = RowGroupAccessPlanFilter::new(ParquetAccessPlan::new_all(1));
+        row_groups.prune_by_bloom_filters(
+            &pruning_predicate,
+            &metrics,
+            &[bloom_statistics],
+        );
+
+        // An evaluation failure is conservative: retain the row group, report
+        // the error separately, and do not call the result a Bloom match.
+        assert_pruned(row_groups, ExpectedPruning::Some(vec![0]));
+        assert_eq!(metrics.predicate_evaluation_errors.value(), 1);
+        assert_eq!(metrics.row_groups_pruned_bloom_filter.pruned(), 0);
+        assert_eq!(metrics.row_groups_pruned_bloom_filter.matched(), 0);
     }
 
     fn get_row_group_meta_data(