diff --git a/AirlockTools.py b/AirlockTools.py
index 30eed4e..da7a9ea 100644
--- a/AirlockTools.py
+++ b/AirlockTools.py
@@ -211,7 +211,7 @@ def menu_prepare_to_enforce():
 		print(ct.colorText("     Remove the rows containing path exclusions you do not approve of" , "cyan"))
 		print(ct.colorText("     When complete, save the csv file to the directory 'manuallyapproved' and choose this option to generate the preflight lists", "cyan"))	
 
-		if os.path.isfile(f"manuallyapproved\\paths_needing_review_{first_policy}_{second_policy}.csv") and os.path.isfile("dataframe_csv\\hashdestination_{first_policy}_{second_policy}.csv") and os.path.isfile(f"dataframe_csv\\addtochildpolicy_{first_policy}_{second_policy}.csv") and os.path.isfile(f"dataframe_csv\\addtobaseline_{first_policy}_{second_policy}.csv"):
+		if os.path.isfile(f"manuallyapproved\\df_paths_needing_review_{first_policy}_{second_policy}.csv") and os.path.isfile("dataframe_csv\\df_hashdestination_{first_policy}_{second_policy}.csv") and os.path.isfile(f"dataframe_csv\\df_addtochildpolicy_{first_policy}_{second_policy}.csv") and os.path.isfile(f"dataframe_csv\\f_addtobaseline_{first_policy}_{second_policy}.csv"):
 			print(ct.colorText("  [✓]  This step has been completed","green"))
 		else:
 			print(ct.colorText("  [✗]  This step has not been completed","red"))
@@ -332,8 +332,35 @@ def menu_prepare_to_enforce():
 				print(ct.colorText(f"Please manually approve hashes prior to this step","red"))
 
 		
-		elif choice == "4":
-			pass
+		elif choice == "7":
+			if os.path.exists(f"manuallyapproved\\df_paths_needing_review_{first_policy}_{second_policy}.csv"):
+				df_approved = tryToReadCSV(f"manuallyapproved\\df_paths_needing_review_{first_policy}_{second_policy}.csv")
+				df_eligible = tryToReadCSV(f"dataframe_csv\\df_paths_needing_review_{first_policy}_{second_policy}.csv")
+				df_ineligible = tryToReadCSV(f"dataframe_csv\\df_path_ineligible_{first_policy}_{second_policy}.csv")
+
+				approved_set = set([tuple(map(tuple, row)) for row in df_approved.values])
+
+				# Identify rows in eligible that are not in approved
+				not_approved_rows = df_eligible[~df_eligible.apply(lambda row: tuple(map(tuple, row)) in approved_set, axis=1)]
+
+				# Append these rows to ineligible
+				df_ineligible= pd.concat([df_ineligible, not_approved_rows], ignore_index=True)
+
+				df_approved.to_csv(f"preflight\\Approved_Path_Exclusions_{first_policy}_{second_policy}.csv")
+				ct.style_dataframe_dark(df_approved, f"preflight\\Approved_Path_Exclusions_{first_policy}_{second_policy}.html")
+
+				#Seperate out what we arent excluding by path into those that will go into the baseline, and those that will b added to the child. 
+				df_addtobaseline = df_ineligible[df_ineligible['reputation status'] == 'KNOWN']
+				df_addtobaseline.to_csv(f"preflight\\Add_to_Baseline_{first_policy}_{second_policy}.csv", index=False)
+				ct.style_dataframe_dark(df_addtobaseline, f"preflight\\Add_to_Baseline_{first_policy}_{second_policy}.html")
+
+				df_addtochildpolicy = df_ineligible[df_ineligible['reputation status'] == 'UNKNOWN']
+				df_addtochildpolicy.to_csv(f"preflight\\Add_to_Child_Policy_{first_policy}_{second_policy}.csv", index=False)
+				ct.style_dataframe_dark(df_addtochildpolicy, f"preflight\\Add_to_Child_Policy_{first_policy}_{second_policy}.html")
+		
+			else:
+				print(ct.colorText(f"Please manually approve suggested paths prior to this step","red"))
+