diff --git a/mc3/plots/posterior.py b/mc3/plots/posterior.py
index ff940a7..1e3580a 100644
--- a/mc3/plots/posterior.py
+++ b/mc3/plots/posterior.py
@@ -193,6 +193,7 @@ def _pairwise(
         hist, hist_xran, axes, ranges, estimates,
         palette, nlevels, absolute_dens, lmax,
         linewidth, theme, alpha=0.8, clear=True,
+        swap_axes=False,
     ):
     """
     Lowest-lever routine to plot pair-wise posterior distributions.
@@ -206,13 +207,19 @@ def _pairwise(
     for icol in range(npars-1):
         for irow in range(icol, npars-1):
             ax = axes[irow,icol]
+            if swap_axes:
+                row, col = icol, irow+1
+                histo = hist[col-1,row].T
+            else:
+                row, col = irow+1, icol
+                histo = hist[row-1,col]
             if clear:
                 ax.clear()
             extent = (
-                hist_xran[icol,0],
-                hist_xran[icol,-1],
-                hist_xran[irow+1,0],
-                hist_xran[irow+1,-1],
+                hist_xran[col, 0],
+                hist_xran[col, -1],
+                hist_xran[row, 0],
+                hist_xran[row, -1],
             )
             levels = np.zeros(nlevels+1)
             levels[1:] = np.linspace(1.0, lmax[irow,icol], nlevels)
@@ -220,29 +227,30 @@ def _pairwise(
             colors[0,3] = 0.0
             colors[1,3] = 0.75*alpha
             cont = ax.contourf(
-                hist[irow,icol],
+                histo,
                 colors=colors, levels=levels,
                 origin='lower', extent=extent,
             )
-            edge_color = to_rgba(theme.color, alpha=0.65)
-            for c in cont.collections:
-                c.set_edgecolor(edge_color)
-                c.set_linewidth(0.1)
-            cont.collections[0].set_edgecolor((1,1,1,0))
-            if estimates[icol] is not None:
+            edge_color = to_rgba(theme.color, alpha=0.25)
+            edge_colors = [edge_color for _ in cont.get_paths()]
+            edge_colors[0] = (1,1,1,0)
+            cont.set_edgecolor(edge_colors)
+            cont.set_linewidth(0.1)
+
+            if estimates[col] is not None:
                 ax.axvline(
-                    estimates[icol],
+                    estimates[col],
                     dashes=(9,2), lw=linewidth, color=theme.dark_color,
                 )
-            if estimates[irow+1] is not None:
+            if estimates[row] is not None:
                 ax.axhline(
-                    estimates[irow+1],
+                    estimates[row],
                     dashes=(9,2), lw=linewidth, color=theme.dark_color,
                 )
-            if ranges[icol] is not None:
-                ax.set_xlim(ranges[icol])
-            if ranges[irow] is not None:
-                ax.set_ylim(ranges[irow+1])
+            if ranges[col] is not None:
+                ax.set_xlim(ranges[col])
+            if ranges[row] is not None:
+                ax.set_ylim(ranges[row])
 
 
 def _plot_marginal(obj):
@@ -302,7 +310,11 @@ def _plot_pairwise(obj):
     for icol in range(npars-1):
         for irow in range(icol, npars-1):
             ax = obj.pair_axes[irow,icol]
-            h = nx*irow + icol + 1 + npars*int(obj.plot_marginal)
+            if obj.orientation == 'vertical':
+                h = nx*irow + icol + 1 + npars*int(obj.plot_marginal)
+            else:
+                h = 2 + (nx+int(obj.plot_marginal))*icol + irow - icol
+
             ax_position = subplot(
                 obj.rect, obj.margin, h, nx, nx, obj.ymargin, dry=True,
             )
@@ -495,7 +507,7 @@ def __set__(self, obj, value):
         setattr(obj.source, var_name, value)
 
 
-class Marginal(object):
+class Marginal():
     """A mostly-interactive marginal posterior plotting object."""
     # Soft-update properties:
     pnames = SoftUpdate()
@@ -625,6 +637,48 @@ def plot(
         if savefile is not None:
             self.fig.savefig(savefile, dpi=300)
 
+    def overplot(self, post, labels=None, nlevels=4, alpha=0.4):
+        """
+        Overplot additional posteriors in the same figure.
+
+        This method is still work in progress!
+        Note that a call to self.update() or even soft updates
+        will remove all/some of the overplot data. In such case
+        the user would need to make a new call to self.overplot().
+        It is also recommended to set show_estimates=False to
+        prevent over-crowding the figures.
+
+        Parameters
+        ----------
+        posts: 1D iterable of Posterior objects
+            Currently there are no checks that these new posteriors
+            have the same parameters (nor same statistics) as self.
+            The user needs to make sure they are all compartible.
+        labels: 1D iterable of strings
+            Labels for each posterior.  Note that if provided, the
+            length of labels has to be one more than posts, because
+            it also contains the label for self.
+        """
+        if '_like' in post.statistics:
+            hpd_min = post.hpd_min
+        else:
+            hpd_min = None
+
+        estimates = post.estimates
+        if not self.show_estimates:
+            estimates = [None for _ in estimates]
+
+        _histogram(
+            post.posterior, estimates, post.ranges,
+            self.hist_axes, self.bins,
+            post.pdf, post.xpdf,
+            hpd_min, post.low_bounds, post.high_bounds,
+            self.linewidth, post.theme,
+            post.orientation,
+            top_pad=1.25,
+            clear=False,
+        )
+
 
 class Figure(Marginal):
     """A mostly-interactive pair-wise posterior plotting object."""
@@ -756,6 +810,7 @@ def plot(
             self.lmax,
             self.linewidth,
             self.theme,
+            swap_axes=self.orientation=='upper right',
         )
 
         # The colorbar: