diff --git a/py-scripts/tools/mine_regression_results.py b/py-scripts/tools/mine_regression_results.py
new file mode 100755
index 00000000..7f210eed
--- /dev/null
+++ b/py-scripts/tools/mine_regression_results.py
@@ -0,0 +1,65 @@
+#!/usr/bin/env python3
+import pandas as pd
+import argparse
+
+
+class MineRegression:
+    def __init__(self,
+                 system_information=None,
+                 save_csv=False):
+        self.df = None
+        self.system_info = system_information
+        self.save_csv = save_csv
+
+    def generate_csv(self):
+        if self.system_info:
+            systems = pd.read_csv(self.system_info)
+            ips = systems['Machine']
+        else:
+            system_info = {'192.168.92.18': ['3.7.7', '5.4.4', 'F30', '.local'],
+                           '192.168.92.12': ['3.9.7', '5.4.4', 'F34', '.local'],
+                           '192.168.93.51': ['3.7.7', '5.4.4', 'F30', 'venv'],
+                           '192.168.92.15': ['3.6.6', '5.4.4', 'F27', '.local']}
+            ips = list(system_info.keys())
+            systems = pd.DataFrame(system_info).transpose().reset_index()
+            systems.columns = ['Machine', 'Python version', 'LF version', 'Fedora version', 'environment']
+        results = [pd.read_html('http://%s/html-reports/latest.html' % url)[0] for url in ips]
+        for result in list(range(0, len(ips))):
+            results[result]['Machine'] = ips[result]
+        self.df = pd.concat(results)
+        self.df = pd.merge(self.df, systems, on='Machine')
+        self.df = self.df[self.df['STDOUT'] == 'STDOUT']
+
+    def generate_report(self):
+        system_variations = self.df[['Python version', 'LF version', 'Fedora version', 'environment']].drop_duplicates().reset_index(
+            drop=True)
+        errors = list()
+        for index in system_variations.index:
+            variation = system_variations.iloc[index]
+            result = self.df.loc[self.df[['Python version', 'LF version', 'Fedora version', 'environment']].isin(dict(
+                variation).values()).all(axis=1), :].dropna(subset=['STDERR']).shape[0]
+            errors.append(result)
+        system_variations['errors'] = errors
+        if self.save_csv:
+            system_variations.to_csv('regression_suite_results.csv')
+        else:
+            print(system_variations.sort_values('errors'))
+
+
+def main():
+    parser = argparse.ArgumentParser(description='Compare regression results from different systems')
+    parser.add_argument('--system_info', help='location of system information csv', default=None)
+    parser.add_argument('--save_csv', help='save CSV of results', default=False)
+
+    args = parser.parse_args()
+
+    Miner = MineRegression(system_information=args.system_info,
+                           save_csv=args.save_csv)
+
+    Miner.generate_csv()
+
+    Miner.generate_report()
+
+
+if __name__ == '__main__':
+    main()