diff --git a/matgl/cli.py b/matgl/cli.py
index 265ebbdd..6778120f 100644
--- a/matgl/cli.py
+++ b/matgl/cli.py
@@ -8,6 +8,7 @@
 import warnings
 
 import numpy as np
+import torch
 from pymatgen.core.structure import Structure
 from pymatgen.ext.matproj import MPRester
 
@@ -73,10 +74,27 @@ def predict_structure(args):
     """
     model = matgl.load_model(args.model)
     if args.infile:
-        for f in args.infile:
-            structure = Structure.from_file(f)
-            val = model.predict_structure(structure)
-            print(f"{args.model} prediction for {f}: {val}.")
+        if args.model == "MEGNet-MP-2019.4.1-BandGap-mfi":
+            state_dict = ["PBE", "GLLB-SC", "HSE", "SCAN"]
+            if len(args.infile) == 1 or not args.infile[1].isdigit():
+                print(
+                    "Error: the multi-fidelity MEGNet bandgap model requires the first argument"
+                    "as structure file and the second arguments as state label (int) iteratively!!"
+                )
+                exit()
+            for count in range(0, len(args.infile), 2):
+                structure = Structure.from_file(args.infile[count])
+                val = model.predict_structure(structure, torch.tensor(int(args.infile[count + 1])))
+                print(
+                    f"{args.model} prediction for {args.infile[count]} with "
+                    f"{state_dict[int(args.infile[count + 1])]} bandgap: {val} eV."
+                )
+
+        else:
+            for f in args.infile:
+                structure = Structure.from_file(f)
+                val = model.predict_structure(structure)
+                print(f"{args.model} prediction for {f}: {val} eV/atom.")
     if args.mpids:
         mpr = MPRester()
         for mid in args.mpids: