diff --git a/crates/polars-parquet/src/arrow/read/statistics/mod.rs b/crates/polars-parquet/src/arrow/read/statistics/mod.rs
index d9210abcb5aa..22ba71caba17 100644
--- a/crates/polars-parquet/src/arrow/read/statistics/mod.rs
+++ b/crates/polars-parquet/src/arrow/read/statistics/mod.rs
@@ -3,7 +3,7 @@ use std::collections::VecDeque;
 
 use arrow::array::*;
 use arrow::datatypes::{ArrowDataType, Field, IntervalUnit, PhysicalType};
-use arrow::types::i256;
+use arrow::types::{f16, i256, NativeType};
 use arrow::with_match_primitive_type_full;
 use ethnum::I256;
 use polars_error::{polars_bail, PolarsResult};
@@ -28,6 +28,7 @@ mod struct_;
 mod utf8;
 
 use self::list::DynMutableListArray;
+use super::PrimitiveLogicalType;
 
 /// Arrow-deserialized parquet Statistics of a file
 #[derive(Debug, PartialEq)]
@@ -549,6 +550,37 @@ fn push(
     }
 }
 
+pub fn cast_statistics(
+    statistics: ParquetStatistics,
+    primitive_type: &ParquetPrimitiveType,
+    output_type: &ArrowDataType,
+) -> ParquetStatistics {
+    use {ArrowDataType as DT, PrimitiveLogicalType as PT};
+
+    match (primitive_type.logical_type, output_type) {
+        (Some(PT::Float16), DT::Float32) => {
+            let statistics = statistics.expect_fixedlen();
+
+            let primitive_type = primitive_type.clone();
+
+            ParquetStatistics::Float(PrimitiveStatistics::<f32> {
+                primitive_type,
+                null_count: statistics.null_count,
+                distinct_count: statistics.distinct_count,
+                min_value: statistics
+                    .min_value
+                    .as_ref()
+                    .map(|v| f16::from_le_bytes([v[0], v[1]]).to_f32()),
+                max_value: statistics
+                    .max_value
+                    .as_ref()
+                    .map(|v| f16::from_le_bytes([v[0], v[1]]).to_f32()),
+            })
+        },
+        _ => statistics,
+    }
+}
+
 /// Deserializes the statistics in the column chunks from a single `row_group`
 /// into [`Statistics`] associated from `field`'s name.
 ///
@@ -562,9 +594,13 @@ pub fn deserialize<'a>(
 
     let mut stats = field_md
         .map(|column| {
+            let primitive_type = &column.descriptor().descriptor.primitive_type;
             Ok((
-                column.statistics().transpose()?,
-                column.descriptor().descriptor.primitive_type.clone(),
+                column
+                    .statistics()
+                    .transpose()?
+                    .map(|stats| cast_statistics(stats, primitive_type, &field.dtype)),
+                primitive_type.clone(),
             ))
         })
         .collect::<PolarsResult<VecDeque<(Option<ParquetStatistics>, ParquetPrimitiveType)>>>()?;
diff --git a/py-polars/tests/unit/io/test_parquet.py b/py-polars/tests/unit/io/test_parquet.py
index 5f73284d9707..d44ed0412e53 100644
--- a/py-polars/tests/unit/io/test_parquet.py
+++ b/py-polars/tests/unit/io/test_parquet.py
@@ -2041,7 +2041,7 @@ def test_conserve_sortedness(
     )
 
 
-def test_decode_f16() -> None:
+def test_f16() -> None:
     values = [float("nan"), 0.0, 0.5, 1.0, 1.5]
 
     table = pa.Table.from_pydict(
@@ -2050,10 +2050,22 @@ def test_decode_f16() -> None:
         }
     )
 
+    df = pl.Series("x", values, pl.Float32).to_frame()
+
     f = io.BytesIO()
     pq.write_table(table, f)
 
     f.seek(0)
-    df = pl.read_parquet(f)
+    assert_frame_equal(pl.read_parquet(f), df)
+
+    f.seek(0)
+    assert_frame_equal(
+        pl.scan_parquet(f).filter(pl.col.x > 0.5).collect(),
+        df.filter(pl.col.x > 0.5),
+    )
 
-    assert_series_equal(df.get_column("x"), pl.Series("x", values, pl.Float32))
+    f.seek(0)
+    assert_frame_equal(
+        pl.scan_parquet(f).slice(1, 3).collect(),
+        df.slice(1, 3),
+    )