diff --git a/src/boruvkas_algorithm/boruvka.py b/src/boruvkas_algorithm/boruvka.py
index febfa57..da54705 100644
--- a/src/boruvkas_algorithm/boruvka.py
+++ b/src/boruvkas_algorithm/boruvka.py
@@ -1,6 +1,8 @@
 """
 Implement Boruvka's algorithm for finding the minimum spanning tree of a graph.
 """
+import matplotlib.pyplot as plt
+import networkx as nx
 
 from typing import Dict, List, Optional, Tuple
 
@@ -217,6 +219,38 @@ def perform_iteration(
 
         return mst_weight, num_components
 
+    def draw_mst(self, mst_edges: List[Tuple[int, int, int]]) -> None:
+        """
+        Draw the graph with the minimum spanning tree highlighted using
+        networkx.
+
+        Args:
+            mst_edges: A list of edges in the minimum spanning tree.
+        """
+        G = nx.Graph()
+        # Add nodes to the graph.
+        G.add_nodes_from(self.vertices)
+        # Add all edges to the graph with weights.
+        for edge in self.edges:
+            vertex1, vertex2, weight = edge
+            G.add_edge(vertex1, vertex2, weight=weight)
+        pos = nx.spring_layout(G)
+        # Draw the graph edges and highlight the edges in the MST in red.
+        nx.draw_networkx_edges(
+            G, pos, edgelist=self.edges, edge_color="gray", alpha=0.5
+        )
+        nx.draw_networkx_edges(G, pos, edgelist=mst_edges, edge_color="red", width=2)
+        # Draw the graph nodes and labels.
+        nx.draw_networkx_nodes(G, pos, node_size=700, node_color="lightblue")
+        nx.draw_networkx_labels(G, pos)
+        nx.draw_networkx_edge_labels(
+            G, pos, edge_labels={(u, v): d["weight"] for u, v, d in G.edges(data=True)}
+        )
+
+        plt.title("Graph with Minimum Spanning Tree Highlighted")
+        plt.axis("off")
+        plt.show()
+
     def run_boruvkas_algorithm(self):
         """
         Find the minimum spanning tree (MST) of the graph using Boruvka's
@@ -254,12 +288,13 @@ def run_boruvkas_algorithm(self):
                 mst_weight,
             )
 
-        # Summarise the MST found.
+        # Summarise the MST found and draw it.
         print("\nMST found with Boruvka's algorithm.")
         print("MST edges (vertex_1, vertex_2, weight):")
         for edge in sorted(mst_edges):
             print(f"    {edge}")
         print(f"MST weight: {mst_weight}")
+        self.draw_mst(mst_edges)
 
         return mst_weight, mst_edges