diff --git a/src/predict_ltg.py b/src/predict_ltg.py
index 131d7e7fd1c8a20d39ce015fffec98ce8b67dbc6..20ca8bb2754bbf6753b4127e9eff5523c25a368c 100755
--- a/src/predict_ltg.py
+++ b/src/predict_ltg.py
@@ -1374,6 +1374,7 @@ def predict_ltg(filelist,
           try:
             if(make_remap_cache): remap_cache = get_remap_cache(glm_area_def, abi_area_def) #If new corner point, cache info for remapping
             glmgrid = ltg_stats_fcts.get_fed(dt,glmpatt,glmvar=glmvar,remap_cache=remap_cache)
+            glmgrid = glmgrid[0:(endY-startY),0:(endX-startX)] #force it to have the same dims as ABI data 
           except (UnboundLocalError,ValueError):
             logging.critical("Couldn't find FED to make predictions for " + dt.strftime('%Y%m%d-%H%M%S'))
             sys.exit()
@@ -1429,13 +1430,10 @@ def predict_ltg(filelist,
         try:
           if(make_remap_cache): remap_cache = get_remap_cache(glm_area_def, abi_area_def) #If new corner point, cache info for remapping
           fed_data = ltg_stats_fcts.get_fed(dt,glmpatt,glmvar=glmvar,remap_cache=remap_cache)
+          fed_data = fed_data[0:(endY-startY),0:(endX-startX)] #force it to have the same dims as ABI data        
         except (UnboundLocalError,ValueError): #couldn't find fed data
           logging.warning("Couldn't find FED for " + dt.strftime('%Y%m%d-%H%M%S'))
           continue #move on to next line / datetime
-        else:
-          #remap FED data to ABI scene
-          fed_data = pr.kd_tree.resample_nearest(glm_area_def,fed_data,abi_area_def,radius_of_influence=4000,fill_value=-1)
-          fed_data = fed_data.filled(0)
 
     #if saving preds/labels, get accumulation target/truth data
     if(pickle_preds_labs):
@@ -1444,6 +1442,7 @@ def predict_ltg(filelist,
         #Doing this so that we can use the glmpatt with "agg" for --ltg_stats
         glmpatt2 = glmpatt.replace('/agg/','/FED_accum_60min_2km/') if('accum' not in glmpatt) else glmpatt
         fed_accum_data = ltg_stats_fcts.get_fed(dt,glmpatt2,glmvar='FED_accum_60min_2km',remap_cache=remap_cache)
+        fed_accum_data = fed_accum_data[0:(endY-startY),0:(endX-startX)] #force it to have the same dims as ABI data
       except (UnboundLocalError,ValueError):
         logging.error(f"Couldn't find any fed_accum_data near {dt}. Moving on to next datetime.")
         continue
@@ -1637,6 +1636,7 @@ def predict_ltg(filelist,
             try:
               if(make_remap_cache): remap_cache = get_remap_cache(glm_area_def, abi_area_def) #If new corner point, cache info for remapping
               imgdata = ltg_stats_fcts.get_fed(dt,glmpatt,glmvar=glmvar,remap_cache=remap_cache)
+              imgdata = imgdata[0:(endY-startY),0:(endX-startX)] #force it to have the same dims as ABI data
             except (UnboundLocalError,ValueError): #couldn't find fed data
               logging.warning("Couldn't find FED for " + dt.strftime('%Y%m%d-%H%M%S'))
               continue #move on to next line / datetime