diff --git a/Exec/science/xrb_spherical/analysis/front_tracker.py b/Exec/science/xrb_spherical/analysis/front_tracker.py
new file mode 100755
index 0000000000..a8ab843a6d
--- /dev/null
+++ b/Exec/science/xrb_spherical/analysis/front_tracker.py
@@ -0,0 +1,49 @@
+#!/usr/bin/env python3
+
+import sys
+import glob
+import yt
+import numpy as np
+from yt.frontends.boxlib.api import CastroDataset
+
+'''
+This file tracks the flame front and writes them into a txt file.
+
+Usage: ./front_tracker.py plotFiles_*
+'''
+
+def track_flame_front(ds):
+    '''
+    This script tracks the flame front position for a given dataset.
+    It returns a tuple of the form: (Time, Theta)
+    Note: time is in milisecond.
+    '''
+
+    time = ds.current_time.in_units("ms")
+
+    # How to determine the flame front?
+    # 1) Global max temperature: this can be used to track initial
+    # detonation resulted from the initial temperature perturbation
+    # 2) Use vertically averaged max enuc to determine the actual flame front
+
+
+    return timeTheta
+
+
+if __name__ == "__main__":
+
+    ts = sys.argv[1:]
+
+    timeThetaArray = []
+    for fname in ts:
+        ds = CastroDataset(fname)
+
+        # Get tuple in form (theta, time)
+        timeTheta= track_flame_front(ds)
+        timeThetaArray.append(timeTheta)
+
+    # Sort array by time and write to file
+    timeThetaArray.sort()
+    timeThetaArray = np.array(timeThetaArray)
+
+    np.savetxt('front_tracking.dat', timeThetaArray, delimiter=',')