diff --git a/pyproject.toml b/pyproject.toml
index a2637fb7..7c6434d7 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -69,5 +69,7 @@ module = [
     "iminuit.*",
     "mplhep.*",
     "hist.version",
+    "ROOT.*",
+    "coffea.*",
 ]
 ignore_missing_imports = true
diff --git a/src/hist/hist2root.py b/src/hist/hist2root.py
new file mode 100644
index 00000000..0564de2a
--- /dev/null
+++ b/src/hist/hist2root.py
@@ -0,0 +1,105 @@
+from __future__ import annotations
+
+import math
+
+import ROOT
+from coffea import processor
+
+import hist.basehist
+
+
+def convert(hist: hist.basehist.BaseHist, hname: str = "") -> ROOT.TH1D | ROOT.TH2D:
+    """Convert a 1-dimensional or 2-dimensional `Hist` object or a counter to ROOT.TH1D or ROOT.TH2D
+    Parameters
+    ----------
+        hist : Hist
+            A 1-dimensional or 2-dimensional histogram object or a counter
+        hname: new name for the output histogram
+    Returns
+    -------
+        out
+            A ``ROOT.TH1D`` or ``ROOT.TH2D`` object
+    Examples
+    --------
+    Saving histograms in the coffea result into a ROOT file
+
+        result = processor.run_uproot_job(
+            samples,
+            "Events",
+            Analysis(),
+            processor.iterative_executor,
+            {"schema": NanoAODSchema},
+        )
+
+        import ROOT
+        import hist2root
+
+        fOUT = ROOT.TFile.Open('output.root','RECREATE')
+        for k in result.keys():
+            hist2root.convert(result[k],k).Write()
+        fOUT.Close()
+    """
+    if isinstance(hist, processor.defaultdict_accumulator):
+        return convertCounter(hist, hname)
+
+    if len(hist.axes) == 1:
+        return convert2TH1D(hist, hname)
+
+    if len(hist.axes) == 2:
+        return convert2TH2D(hist, hname)
+
+    raise TypeError("Not a known ROOT type")
+
+
+def convertCounter(counter: hist.basehist.BaseHist, hname: str):
+    n = len(counter.keys())
+    out = ROOT.TH1D(hname, "", n, 0, n)
+    for i, key in enumerate(counter.keys()):
+        out.SetBinContent(i + 1, counter[key])
+        out.GetXaxis().SetBinLabel(i + 1, key)
+    return out
+
+
+def convert2TH1D(hist: hist.basehist.BaseHist, hname: str) -> ROOT.TH1D:
+    name = hist.label
+    if len(name) > 0:
+        name = hname
+    title = hist.label
+    axis = hist.axes[0]
+    edges = axis.edges(overflow="none")
+    edgesOFlow = axis.edges(overflow="all")
+
+    out = ROOT.TH1D(name, title, len(edges) - 1, edges)
+    for i in range(0, len(edgesOFlow) - 1):
+        bincenter = edgesOFlow[i] + 0.5 * (edgesOFlow[i + 1] - edgesOFlow[i])
+        x = bincenter
+        w, wsq = hist.values(sumw2=True, overflow="all")[()]
+        out.Fill(x, w[i])
+        out.SetBinError(i, math.sqrt(wsq[i]))
+    return out
+
+
+def convert2TH2D(hist: hist.basehist.BaseHist, hname: str) -> ROOT.TH2D:
+    name = hist.label
+    if len(name) > 0:
+        name = hname
+    title = hist.label
+    axis1 = hist.axes[0]
+    xedges = axis1.edges(overflow="none")
+    xedgesOFlow = axis1.edges(overflow="all")
+    axis2 = hist.axes[1]
+    yedges = axis2.edges(overflow="none")
+    yedgesOFlow = axis2.edges(overflow="all")
+
+    out = ROOT.TH2D(name, title, len(xedges) - 1, xedges, len(yedges) - 1, yedges)
+
+    for i in range(0, len(xedgesOFlow) - 1):
+        xbincenter = xedgesOFlow[i] + 0.5 * (xedgesOFlow[i + 1] - xedgesOFlow[i])
+        x = xbincenter
+        for j in range(0, len(yedgesOFlow) - 1):
+            ybincenter = yedgesOFlow[j] + 0.5 * (yedgesOFlow[j + 1] - yedgesOFlow[j])
+            y = ybincenter
+            w, wsq = hist.values(sumw2=True, overflow="all")[()]
+            out.Fill(x, y, w[j][i])
+            out.SetBinError(i, j, math.sqrt(wsq[j][i]))
+    return out