diff --git a/pyforestscan/visualize.py b/pyforestscan/visualize.py
index fd7b6c2..89b2670 100644
--- a/pyforestscan/visualize.py
+++ b/pyforestscan/visualize.py
@@ -8,7 +8,7 @@ def plot_2d(points, x_dim='X',
             alpha=1.0, point_size=1,
             fig_size=None, fig_title=None,
             slice_dim=None, slice_val=0.0,
-            slice_tolerance=5
+            slice_tolerance=5, save_fname=None
 ):
     """
     Plots a 2D scatter plot of data points with customizable axes, coloring, and display settings.
@@ -29,6 +29,7 @@ def plot_2d(points, x_dim='X',
         slice_val (float): The coordinate value at which to slice the slice_dim dimension.
         slice_tolerance (float): Allowed absolute difference when matching slice_val.
                                  (Helps with floating-point comparisons.)
+        save_fname (str): If provided, will be forwarded to `plt.savefig` to save the figure.
 
     Returns:
         None
@@ -79,10 +80,13 @@ def plot_2d(points, x_dim='X',
     plt.ylabel(y_dim)
     plt.title(fig_title)
     plt.colorbar(label=colorbar_label)
+    if save_fname is not None:
+        plt.savefig(save_fname, dpi=300, bbox_inches='tight')
     plt.show()
 
 
-def plot_metric(title, metric, extent, metric_name=None, cmap='viridis', fig_size=None):
+def plot_metric(title, metric, extent, metric_name=None, cmap='viridis', fig_size=None,
+                save_fname=None):
     """
     Plots a given metric using the provided data and configuration.
 
@@ -100,6 +104,8 @@ def plot_metric(title, metric, extent, metric_name=None, cmap='viridis', fig_siz
         Colormap to be used for the plot. Default is 'viridis'.
     :param fig_size: tuple, optional
         Tuple specifying the size of the figure (width, height). Default is calculated based on the extent.
+    :param save_fname: str, optional
+        If provided, will be forwarded to `plt.savefig` to save the figure.
     :return: None
     :rtype: None
     """
@@ -123,11 +129,13 @@ def plot_metric(title, metric, extent, metric_name=None, cmap='viridis', fig_siz
     plt.title(title)
     plt.xlabel('X')
     plt.ylabel('Y')
+    if save_fname is not None:
+        plt.savefig(save_fname, dpi=300, bbox_inches='tight')
     plt.show()
 
 
 def plot_pad(pad, slice_index=None, axis='x', cmap='viridis',
-             hag_values=None, horizontal_values=None, title=None):
+             hag_values=None, horizontal_values=None, title=None, save_fname=None):
     """
     Plots the plant area density (PAD) data as a 2D image visualization.
 
@@ -153,6 +161,8 @@ def plot_pad(pad, slice_index=None, axis='x', cmap='viridis',
         title: Optional; A string specifying the title of the plot. If None, an
             appropriate default title will be generated based on the input
             parameters.
+        save_fname: Optional; A string that will be forwarded to `plt.savefig` to save
+            the figure.
 
     Returns:
         None. The function visualizes the PAD data using matplotlib.
@@ -227,4 +237,6 @@ def plot_pad(pad, slice_index=None, axis='x', cmap='viridis',
     plt.xlabel(horizontal_axis_label)
     plt.ylabel('dZ')
     plt.tight_layout()
+    if save_fname is not None:
+        plt.savefig(save_fname, dpi=300, bbox_inches='tight')
     plt.show()
\ No newline at end of file