diff --git a/freqtrade/freqai/base_models/FreqaiMultiOutputRegressor.py b/freqtrade/freqai/base_models/FreqaiMultiOutputRegressor.py
index aa5dbe629..a9db81e31 100644
--- a/freqtrade/freqai/base_models/FreqaiMultiOutputRegressor.py
+++ b/freqtrade/freqai/base_models/FreqaiMultiOutputRegressor.py
@@ -36,9 +36,6 @@ class FreqaiMultiOutputRegressor(MultiOutputRegressor):
 
         y = self._validate_data(X="no_validation", y=y, multi_output=True)
 
-        # if is_classifier(self):
-        #     check_classification_targets(y)
-
         if y.ndim == 1:
             raise ValueError(
                 "y must have at least two dimensions for "
@@ -50,19 +47,12 @@ class FreqaiMultiOutputRegressor(MultiOutputRegressor):
         ):
             raise ValueError("Underlying estimator does not support sample weights.")
 
-        # fit_params_validated = _check_fit_params(X, fit_params)
-
         if not fit_params:
             fit_params = [None] * y.shape[1]
 
-        # if not init_models:
-        #     init_models = [None] * y.shape[1]
-
         self.estimators_ = Parallel(n_jobs=self.n_jobs)(
             delayed(_fit_estimator)(
                 self.estimator, X, y[:, i], sample_weight, **fit_params[i]
-                # init_model=init_models[i], eval_set=eval_sets[i],
-                # **fit_params_validated
             )
             for i in range(y.shape[1])
         )
diff --git a/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py b/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py
index a376b2c33..7fa4e293e 100644
--- a/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py
+++ b/freqtrade/freqai/prediction_models/CatboostRegressorMultiTarget.py
@@ -60,6 +60,9 @@ class CatboostRegressorMultiTarget(BaseRegressionModel):
                 {'eval_set': eval_sets[i],  'init_model': init_models[i]})
 
         model = FreqaiMultiOutputRegressor(estimator=cbr)
+        thread_training = self.freqai_info.get('multitarget_parallel_training', False)
+        if thread_training:
+            model.n_jobs = y.shape[1]
         model.fit(X=X, y=y, sample_weight=sample_weight, fit_params=fit_params)
 
         return model
diff --git a/freqtrade/freqai/prediction_models/LightGBMRegressorMultiTarget.py b/freqtrade/freqai/prediction_models/LightGBMRegressorMultiTarget.py
index 7a9b5c36a..37c6bb186 100644
--- a/freqtrade/freqai/prediction_models/LightGBMRegressorMultiTarget.py
+++ b/freqtrade/freqai/prediction_models/LightGBMRegressorMultiTarget.py
@@ -56,9 +56,9 @@ class LightGBMRegressorMultiTarget(BaseRegressionModel):
                  'init_model': init_models[i]})
 
         model = FreqaiMultiOutputRegressor(estimator=lgb)
+        thread_training = self.freqai_info.get('multitarget_parallel_training', False)
+        if thread_training:
+            model.n_jobs = y.shape[1]
         model.fit(X=X, y=y, sample_weight=sample_weight, fit_params=fit_params)
 
-        # model = FreqaiMultiOutputRegressor(estimator=lgb)
-        # model.fit(X=X, y=y, sample_weight=sample_weight, init_models=init_models,
-        #           eval_sets=eval_sets, eval_sample_weight=eval_weights)
         return model
diff --git a/freqtrade/freqai/prediction_models/XGBoostRegressorMultiTarget.py b/freqtrade/freqai/prediction_models/XGBoostRegressorMultiTarget.py
index 38c478c0b..920745ec9 100644
--- a/freqtrade/freqai/prediction_models/XGBoostRegressorMultiTarget.py
+++ b/freqtrade/freqai/prediction_models/XGBoostRegressorMultiTarget.py
@@ -55,6 +55,9 @@ class XGBoostRegressorMultiTarget(BaseRegressionModel):
                  'xgb_model': init_models[i]})
 
         model = FreqaiMultiOutputRegressor(estimator=xgb)
+        thread_training = self.freqai_info.get('multitarget_parallel_training', False)
+        if thread_training:
+            model.n_jobs = y.shape[1]
         model.fit(X=X, y=y, sample_weight=sample_weight, fit_params=fit_params)
 
         return model