diff --git a/google/cloud/bigquery/_versions_helpers.py b/google/cloud/bigquery/_versions_helpers.py
index 50d5961b3..72d4c921d 100644
--- a/google/cloud/bigquery/_versions_helpers.py
+++ b/google/cloud/bigquery/_versions_helpers.py
@@ -26,6 +26,9 @@
 _BQ_STORAGE_OPTIONAL_READ_SESSION_VERSION = packaging.version.Version("2.6.0")
 _MIN_PANDAS_VERSION = packaging.version.Version("1.1.0")
 
+_MIN_PANDAS_VERSION_RANGE = packaging.version.Version("1.5.0")
+_MIN_PYARROW_VERSION_RANGE = packaging.version.Version("10.0.1")
+
 
 class PyarrowVersions:
     """Version comparisons for pyarrow package."""
@@ -234,3 +237,14 @@ def try_import(self, raise_if_error: bool = False) -> Any:
 
 
 PANDAS_VERSIONS = PandasVersions()
+
+# Since RANGE support in pandas requires specific versions
+# of both pyarrow and pandas, we make this a separate
+# constant instead of as a property of PANDAS_VERSIONS
+# or PYARROW_VERSIONS.
+SUPPORTS_RANGE_PYARROW = (
+    PANDAS_VERSIONS.try_import() is not None
+    and PANDAS_VERSIONS.installed_version >= _MIN_PANDAS_VERSION_RANGE
+    and PYARROW_VERSIONS.try_import() is not None
+    and PYARROW_VERSIONS.installed_version >= _MIN_PYARROW_VERSION_RANGE
+)
diff --git a/google/cloud/bigquery/table.py b/google/cloud/bigquery/table.py
index 2f07bcc78..ad1253195 100644
--- a/google/cloud/bigquery/table.py
+++ b/google/cloud/bigquery/table.py
@@ -100,6 +100,12 @@
     "because the necessary `__from_arrow__` attribute is missing."
 )
 
+_RANGE_PYARROW_WARNING = (
+    "Unable to represent RANGE schema as struct using pandas ArrowDtype. Using "
+    "`object` instead. To use ArrowDtype, use pandas >= 1.5 and "
+    "pyarrow >= 10.0.1."
+)
+
 # How many of the total rows need to be downloaded already for us to skip
 # calling the BQ Storage API?
 ALMOST_COMPLETELY_CACHED_RATIO = 0.333
@@ -2279,26 +2285,18 @@ def to_dataframe(
             time_dtype = db_dtypes.TimeDtype()
 
         if range_date_dtype is DefaultPandasDTypes.RANGE_DATE_DTYPE:
-            try:
+            if _versions_helpers.SUPPORTS_RANGE_PYARROW:
                 range_date_dtype = pandas.ArrowDtype(
                     pyarrow.struct(
                         [("start", pyarrow.date32()), ("end", pyarrow.date32())]
                     )
                 )
-            except AttributeError:
-                # pandas.ArrowDtype was introduced in pandas 1.5, but python 3.7
-                # only supports upto pandas 1.3. If pandas.ArrowDtype is not
-                # present, we raise a warning and set range_date_dtype to None.
-                msg = (
-                    "Unable to find class ArrowDtype in pandas, setting "
-                    "range_date_dtype to be None. To use ArrowDtype, please "
-                    "use pandas >= 1.5 and python >= 3.8."
-                )
-                warnings.warn(msg)
+            else:
+                warnings.warn(_RANGE_PYARROW_WARNING)
                 range_date_dtype = None
 
         if range_datetime_dtype is DefaultPandasDTypes.RANGE_DATETIME_DTYPE:
-            try:
+            if _versions_helpers.SUPPORTS_RANGE_PYARROW:
                 range_datetime_dtype = pandas.ArrowDtype(
                     pyarrow.struct(
                         [
@@ -2307,20 +2305,12 @@ def to_dataframe(
                         ]
                     )
                 )
-            except AttributeError:
-                # pandas.ArrowDtype was introduced in pandas 1.5, but python 3.7
-                # only supports upto pandas 1.3. If pandas.ArrowDtype is not
-                # present, we raise a warning and set range_datetime_dtype to None.
-                msg = (
-                    "Unable to find class ArrowDtype in pandas, setting "
-                    "range_datetime_dtype to be None. To use ArrowDtype, "
-                    "please use pandas >= 1.5 and python >= 3.8."
-                )
-                warnings.warn(msg)
+            else:
+                warnings.warn(_RANGE_PYARROW_WARNING)
                 range_datetime_dtype = None
 
         if range_timestamp_dtype is DefaultPandasDTypes.RANGE_TIMESTAMP_DTYPE:
-            try:
+            if _versions_helpers.SUPPORTS_RANGE_PYARROW:
                 range_timestamp_dtype = pandas.ArrowDtype(
                     pyarrow.struct(
                         [
@@ -2329,16 +2319,8 @@ def to_dataframe(
                         ]
                     )
                 )
-            except AttributeError:
-                # pandas.ArrowDtype was introduced in pandas 1.5, but python 3.7
-                # only supports upto pandas 1.3. If pandas.ArrowDtype is not
-                # present, we raise a warning and set range_timestamp_dtype to None.
-                msg = (
-                    "Unable to find class ArrowDtype in pandas, setting "
-                    "range_timestamp_dtype to be None. To use ArrowDtype, "
-                    "please use pandas >= 1.5 and python >= 3.8."
-                )
-                warnings.warn(msg)
+            else:
+                warnings.warn(_RANGE_PYARROW_WARNING)
                 range_timestamp_dtype = None
 
         if bool_dtype is not None and not hasattr(bool_dtype, "__from_arrow__"):