diff --git a/src/conformist/prediction_dataset.py b/src/conformist/prediction_dataset.py
index b55471d..a552aa5 100644
--- a/src/conformist/prediction_dataset.py
+++ b/src/conformist/prediction_dataset.py
@@ -195,6 +195,15 @@ def visualize_class_counts_by_dataset(self):
         # create a bar chart
         ccs = self.class_counts_by_dataset()
 
+        # Get all unique classes
+        all_classes = ccs.index.get_level_values(1).unique()
+
+        # Define a colormap
+        colormap = plt.cm.get_cmap('tab20')
+
+        # Create a dictionary to map each class to a color
+        class_to_color = {cls: colormap(i) for i, cls in enumerate(all_classes)}
+
         # Count how many datasets and create a grid of plots
         num_datasets = len(ccs.index.get_level_values(0).unique())
         fig, axs = plt.subplots(num_datasets, 1, figsize=(10, 8 * num_datasets))
@@ -207,7 +216,6 @@ def visualize_class_counts_by_dataset(self):
 
         # Order datasets by number of items
         ordered_datasets = grouped_ccs.sort_values(ascending=False).index
-        print(type(ordered_datasets))
 
         # For each dataset, create a bar chart
         for i, dataset in enumerate(ordered_datasets):
@@ -219,8 +227,14 @@ def visualize_class_counts_by_dataset(self):
 
             sorted_series = dataset_series.sort_values(ascending=False)
 
+            # Get colors for the bars
+            bar_colors = [class_to_color[cls] for cls in sorted_series.index]
+
             # Plot bar chart with fixed width
-            axs[i].bar(sorted_series.index, sorted_series.values, width=0.5)
+            bars = axs[i].bar(sorted_series.index,
+                              sorted_series.values,
+                              width=0.5,
+                              color=bar_colors)
             axs[i].set_title(dataset)
 
             # Print count above each bar
@@ -228,6 +242,13 @@ def visualize_class_counts_by_dataset(self):
                 if np.isfinite(v):
                     axs[i].text(j, v, str(v), ha='center', va='bottom')
 
+            # Remove x-axis labels
+            axs[i].set_xticklabels([])
+
+            # Add legend
+            if i == 0:
+                axs[i].legend(bars, sorted_series.index, title="Classes")
+
         # show the plot
         plt.savefig(f'{self.output_dir}/class_counts_by_dataset.png',
                     bbox_inches='tight')