diff --git a/src/proloaf/event_logging.py b/src/proloaf/event_logging.py
index 0d2962245e7727364d1dd701bac03bf6c126ae7b..567816232f24116532278017350ea584f0233dd8 100644
--- a/src/proloaf/event_logging.py
+++ b/src/proloaf/event_logging.py
@@ -1,10 +1,13 @@
 import os
 import logging
 import logging.config
+import functools
+import time
 from proloaf.confighandler import read_config
 
 MAIN_PATH = os.path.dirname(os.path.abspath(__file__))
 
+
 def create_event_logger(
         name: str,
         config_path: os.path = os.path.join(MAIN_PATH, 'event_logging_conf.json'),
@@ -56,3 +59,22 @@ def create_event_logger(
             logger = logging.getLogger(name)
 
     return logger
+
+
+def timer(logger: logging.Logger):
+    """
+    Decorator which passes the runtime of the decorated function to a logger.
+    The logger then prints the name and runtime of the function, if the logger is specified to print statements
+    of rank "INFO".
+    """
+    def decorator(func):
+        @functools.wraps(func)
+        def wrapper_timer(*args, **kwargs):
+            start_time = time.perf_counter()
+            value = func(*args, **kwargs)
+            end_time = time.perf_counter()
+            run_time = end_time - start_time
+            logger.info(f"Finished {func.__name__!r} in {run_time:.4f} secs")
+            return value
+        return wrapper_timer
+    return decorator
diff --git a/src/proloaf/modelhandler.py b/src/proloaf/modelhandler.py
index 5b4b77c9ba1dc2b42958e206f4f087483d1e4bbc..eb9e82f09f0aa27ec1b01e94fc9416a2ffe19e6f 100644
--- a/src/proloaf/modelhandler.py
+++ b/src/proloaf/modelhandler.py
@@ -45,6 +45,7 @@ from proloaf.loghandler import (
     end_tensorboard,
 )
 from proloaf.event_logging import create_event_logger
+from proloaf.event_logging import timer
 
 logger = create_event_logger(__name__)
 
@@ -861,6 +862,7 @@ class ModelHandler:
         end_tensorboard(tb, hparams, values)
         return temp_model_wrap
 
+    @timer(logger)
     def fit(
         self,
         train_data: proloaf.tensorloader.TimeSeriesData,
@@ -900,6 +902,7 @@ class ModelHandler:
             )
         return self
 
+    @timer(logger)
     def predict(self, inputs_enc: torch.Tensor, inputs_dec: torch.Tensor):
         """
         Get the predictions for the given model and data