diff --git a/src/access/profiling/manager.py b/src/access/profiling/manager.py
index d0ad053..5af74db 100644
--- a/src/access/profiling/manager.py
+++ b/src/access/profiling/manager.py
@@ -11,6 +11,7 @@
 
 from access.profiling.experiment import ProfilingExperiment, ProfilingExperimentStatus, ProfilingLog
 from access.profiling.metrics import ProfilingMetric
+from access.profiling.plotting_utils import plot_bar_metrics
 from access.profiling.scaling import plot_scaling_metrics
 
 logger = logging.getLogger(__name__)
@@ -238,3 +239,55 @@ def plot_scaling_data(
             scaling_data.append(component_data)
 
         return plot_scaling_metrics(scaling_data, metric)
+
+    def plot_bar_chart(
+        self,
+        components: list[str],
+        regions: list[list[str]],
+        metric: ProfilingMetric,
+        region_relabel_map: dict | None = None,
+        experiments: list[str] | None = None,
+        show: bool = True,
+    ) -> Figure:
+        """Plots a bar chart of a profiling metric over regions, grouped by experiment.
+
+        Regions are placed along the x-axis. Within each region group, there is one bar per
+        experiment, coloured by experiment name.
+
+        Args:
+            components (list[str]): List of component names to include.
+            regions (list[list[str]]): List of regions to include for each component.
+            metric (ProfilingMetric): Metric to plot.
+            region_relabel_map (dict | None): Optional mapping to relabel regions in the plot.
+            experiments (list[str] | None): Optional list of experiment names to include. If None, all experiments
+                are included.
+            show (bool): Whether to show the generated plot. Default: True.
+
+        Returns:
+            Figure: The Matplotlib figure containing the bar chart.
+
+        Raises:
+            ValueError: If no profiling data is found for a specified component in any experiment.
+        """
+        exp_names = experiments if experiments is not None else list(self.data.keys())
+        relabel = region_relabel_map or {}
+
+        # Build a lookup from display label to (component, original_region) and preserve input order.
+        region_info: list[tuple[str, str, str]] = []  # (component, original_region, display_label)
+        for component, component_regions in zip(components, regions, strict=True):
+            for region in component_regions:
+                region_info.append((component, region, relabel.get(region, region)))
+        region_labels = [label for _, _, label in region_info]
+
+        # Extract metric values per experiment, reading directly from the datasets
+        bar_data: dict[str, list[float]] = {}
+        for exp_name in exp_names:
+            values = []
+            for component, region, _ in region_info:
+                ds = self.data[exp_name].get(component)
+                if ds is None:
+                    raise ValueError(f"No profiling data found for component '{component}' in experiment '{exp_name}'.")
+                values.append(float(ds[metric].sel(region=region).pint.dequantify().values))
+            bar_data[exp_name] = values
+
+        return plot_bar_metrics(bar_data, region_labels, metric, show=show)
diff --git a/src/access/profiling/plotting_utils.py b/src/access/profiling/plotting_utils.py
index 227c415..b39113c 100644
--- a/src/access/profiling/plotting_utils.py
+++ b/src/access/profiling/plotting_utils.py
@@ -1,6 +1,11 @@
 # Copyright 2025 ACCESS-NRI and contributors. See the top-level COPYRIGHT file for details.
 # SPDX-License-Identifier: Apache-2.0
 
+import matplotlib.pyplot as plt
+from matplotlib.figure import Figure
+
+from access.profiling.metrics import ProfilingMetric
+
 
 def calculate_column_widths(table_data: list[list], first_col_fraction: float = None) -> list:
     """Calculate column widths based on content character length and required width for first column.
@@ -61,3 +66,51 @@ def calculate_column_widths(table_data: list[list], first_col_fraction: float =
         col_widths = [length / total_length for length in max_lengths]
 
     return col_widths
+
+
+def plot_bar_metrics(
+    data: dict[str, list[float]],
+    region_labels: list[str],
+    metric: ProfilingMetric,
+    show: bool = True,
+) -> Figure:
+    """Plots a grouped bar chart of a profiling metric over regions.
+
+    Regions are placed along the x-axis. Within each region group, there is one bar per
+    experiment, coloured by experiment name.
+
+    Args:
+        data (dict[str, list[float]]): Mapping of experiment name to a list of metric values,
+            one per region (in the same order as ``region_labels``).
+        region_labels (list[str]): Ordered list of region display labels for the x-axis.
+        metric (ProfilingMetric): The metric being plotted (used for axis labels and title).
+        show (bool): Whether to call ``plt.show()``. Default: True.
+
+    Returns:
+        Figure: The Matplotlib figure containing the bar chart.
+    """
+    exp_names = list(data.keys())
+    n_experiments = len(exp_names)
+    n_regions = len(region_labels)
+
+    fig, ax = plt.subplots(figsize=(max(8, n_experiments * n_regions * 0.8), 6))
+    bar_width = 0.8 / n_experiments
+    group_positions = list(range(n_regions))
+
+    for i, exp_name in enumerate(exp_names):
+        offsets = [pos + (i - (n_experiments - 1) / 2) * bar_width for pos in group_positions]
+        ax.bar(offsets, data[exp_name], width=bar_width, label=exp_name)
+
+    ax.set_xticks(group_positions)
+    ax.set_xticklabels(region_labels)
+    ax.set_xlabel("Region")
+    ax.set_ylabel(f"{metric.name} ({metric.units})")
+    ax.set_title(f"{metric.description}")
+    ax.legend(title="Experiment")
+    ax.grid(axis="y", linestyle="--", alpha=0.7)
+    fig.tight_layout()
+
+    if show:
+        plt.show()
+
+    return fig
diff --git a/tests/test_manager.py b/tests/test_manager.py
index 61d957a..c86ba4f 100644
--- a/tests/test_manager.py
+++ b/tests/test_manager.py
@@ -307,3 +307,66 @@ def test_scaling_data(mock_plot, scaling_data):
     assert component_data[count].sel(region="Total").values.tolist() == [1, 1]
     assert component_data[tavg].sel(region="Total").values.tolist() == [600365.0, 300182.5]
     assert mock_plot.call_args.args[1] == tavg
+
+
+@mock.patch("access.profiling.manager.plot_bar_metrics")
+def test_bar_chart_data(mock_plot, scaling_data):
+    """Test the plot_bar_chart method of ProfilingManager.
+
+    This test checks that bar chart data is correctly extracted from the datasets and that the
+    plotting function is called with the right arguments.
+    """
+    paths, ncpus, datasets = scaling_data
+    manager = MockProfilingManager(paths, ncpus, datasets)
+
+    # Test plotting bar chart for non-existing component
+    with pytest.raises(ValueError):
+        manager.plot_bar_chart(
+            components=["non_existing_component"],
+            regions=[["Region 1"]],
+            metric=tavg,
+        )
+
+    # Test plotting bar chart with region selection, relabelling, and experiment filtering
+    manager.plot_bar_chart(
+        components=["component"],
+        regions=[["Region 1", "Region 2"]],
+        metric=tavg,
+        region_relabel_map={"Region 1": "Total"},
+        experiments=["1cpu", "4cpu"],
+    )
+    assert mock_plot.call_count == 1
+
+    # Verify the data dict passed to plot_bar_metrics
+    bar_data = mock_plot.call_args.args[0]
+    assert isinstance(bar_data, dict)
+    assert set(bar_data.keys()) == {"1cpu", "4cpu"}
+    assert bar_data["1cpu"] == pytest.approx([600365.0, 2.345388])
+    assert bar_data["4cpu"] == pytest.approx([300182.5, 1.172694])
+
+    # Verify region labels
+    region_labels = mock_plot.call_args.args[1]
+    assert region_labels == ["Total", "Region 2"]
+
+    # Verify metric
+    assert mock_plot.call_args.args[2] == tavg
+
+    # Verify show kwarg is passed through
+    assert mock_plot.call_args.kwargs["show"] is True
+
+
+@mock.patch("access.profiling.manager.plot_bar_metrics")
+def test_bar_chart_all_experiments(mock_plot, scaling_data):
+    """Test plot_bar_chart includes all experiments when none are specified."""
+    paths, ncpus, datasets = scaling_data
+    manager = MockProfilingManager(paths, ncpus, datasets)
+
+    manager.plot_bar_chart(
+        components=["component"],
+        regions=[["Region 1"]],
+        metric=tavg,
+        show=False,
+    )
+    bar_data = mock_plot.call_args.args[0]
+    assert set(bar_data.keys()) == {"1cpu", "4cpu", "2cpu"}
+    assert mock_plot.call_args.kwargs["show"] is False
diff --git a/tests/test_plotting_utils.py b/tests/test_plotting_utils.py
index 1193463..e07f976 100644
--- a/tests/test_plotting_utils.py
+++ b/tests/test_plotting_utils.py
@@ -1,9 +1,13 @@
 # Copyright 2025 ACCESS-NRI and contributors. See the top-level COPYRIGHT file for details.
 # SPDX-License-Identifier: Apache-2.0
 
+from unittest import mock
+
 import pytest
+from matplotlib.figure import Figure
 
-from access.profiling.plotting_utils import calculate_column_widths
+from access.profiling.metrics import tavg
+from access.profiling.plotting_utils import calculate_column_widths, plot_bar_metrics
 
 
 @pytest.fixture(scope="module")
@@ -75,3 +79,64 @@ def test_invalid_tables(nonrectangular_table_data, singlerow_table_data, singlec
         calculate_column_widths(singlerow_table_data)
     with pytest.raises(ValueError):
         calculate_column_widths(singlecol_table_data)
+
+
+def test_plot_bar_metrics_returns_figure():
+    """Test that plot_bar_metrics returns a Figure with correct structure."""
+    data = {
+        "exp_A": [100.0, 50.0],
+        "exp_B": [80.0, 40.0],
+    }
+    region_labels = ["Region 1", "Region 2"]
+
+    fig = plot_bar_metrics(data, region_labels, tavg, show=False)
+
+    assert isinstance(fig, Figure)
+    ax = fig.axes[0]
+
+    # Check axis labels and title
+    assert ax.get_xlabel() == "Region"
+    assert tavg.name in ax.get_ylabel()
+    assert str(tavg.units) in ax.get_ylabel()
+    assert ax.get_title() == tavg.description
+
+    # Check x-tick labels match the region labels
+    tick_labels = [t.get_text() for t in ax.get_xticklabels()]
+    assert tick_labels == region_labels
+
+    # Check legend shows experiment names
+    legend_labels = [t.get_text() for t in ax.get_legend().get_texts()]
+    assert legend_labels == ["exp_A", "exp_B"]
+
+    # Check correct number of bars: 2 experiments * 2 regions = 4 bars
+    assert len(ax.patches) == 4
+
+    # matplotlib groups bars by series: first all exp_A bars, then all exp_B bars
+    heights = [p.get_height() for p in ax.patches]
+    assert heights == pytest.approx([100.0, 50.0, 80.0, 40.0])
+
+
+def test_plot_bar_metrics_single_experiment():
+    """Test plot_bar_metrics with a single experiment."""
+    data = {"exp_A": [10.0, 20.0, 30.0]}
+    region_labels = ["R1", "R2", "R3"]
+
+    fig = plot_bar_metrics(data, region_labels, tavg, show=False)
+    ax = fig.axes[0]
+
+    assert len(ax.patches) == 3
+    legend_labels = [t.get_text() for t in ax.get_legend().get_texts()]
+    assert legend_labels == ["exp_A"]
+
+
+@mock.patch("access.profiling.plotting_utils.plt.show")
+def test_plot_bar_metrics_show(mock_show):
+    """Test that plt.show() is called when show=True and not called when show=False."""
+    data = {"exp_A": [10.0]}
+    region_labels = ["R1"]
+
+    plot_bar_metrics(data, region_labels, tavg, show=True)
+    assert mock_show.call_count == 1
+
+    plot_bar_metrics(data, region_labels, tavg, show=False)
+    assert mock_show.call_count == 1  # No additional call