diff --git a/example_data/config.yaml b/example_data/config.yaml
index 46f34c3..08a98f2 100644
--- a/example_data/config.yaml
+++ b/example_data/config.yaml
@@ -117,7 +117,8 @@ train:
     size:
       weight: 0.1
   logger:
-    logger_type: dvclive
+    logger_type: mlflow
+    tracking_uri: http://localhost:5000
   augmentations:
     steps:
       - augmentation_type: mix_audio
diff --git a/pyproject.toml b/pyproject.toml
index 3bee649..8170836 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -91,6 +91,9 @@ dev = [
 dvclive = [
     "dvclive>=3.48.2",
 ]
+mlflow = [
+    "mlflow>=3.1.1",
+]
 
 [tool.ruff]
 line-length = 79
diff --git a/src/batdetect2/train/logging.py b/src/batdetect2/train/logging.py
index fb70c78..26fa64d 100644
--- a/src/batdetect2/train/logging.py
+++ b/src/batdetect2/train/logging.py
@@ -1,4 +1,4 @@
-from typing import Annotated, Literal, Optional, Union
+from typing import Annotated, Any, Literal, Optional, Union
 
 from lightning.pytorch.loggers import Logger
 from pydantic import Field
@@ -34,8 +34,23 @@ class TensorBoardLoggerConfig(BaseConfig):
     flush_logs_every_n_steps: Optional[int] = None
 
 
+class MLFlowLoggerConfig(BaseConfig):
+    logger_type: Literal["mlflow"] = "mlflow"
+    experiment_name: str = "default"
+    run_name: Optional[str] = None
+    save_dir: Optional[str] = "./mlruns"
+    tracking_uri: Optional[str] = None
+    tags: Optional[dict[str, Any]] = None
+    log_model: bool = False
+
+
 LoggerConfig = Annotated[
-    Union[DVCLiveConfig, CSVLoggerConfig, TensorBoardLoggerConfig],
+    Union[
+        DVCLiveConfig,
+        CSVLoggerConfig,
+        TensorBoardLoggerConfig,
+        MLFlowLoggerConfig,
+    ],
     Field(discriminator="logger_type"),
 ]
 
@@ -82,10 +97,31 @@ def create_tensorboard_logger(config: TensorBoardLoggerConfig) -> Logger:
     )
 
 
+def create_mlflow_logger(config: MLFlowLoggerConfig) -> Logger:
+    try:
+        from lightning.pytorch.loggers import MLFlowLogger
+    except ImportError as error:
+        raise ValueError(
+            "MLFlow is not installed and cannot be used for logging. "
+            "Make sure you have it installed by running `pip install mlflow` "
+            "or `uv add mlflow`"
+        ) from error
+
+    return MLFlowLogger(
+        experiment_name=config.experiment_name,
+        run_name=config.run_name,
+        save_dir=config.save_dir,
+        tracking_uri=config.tracking_uri,
+        tags=config.tags,
+        log_model=config.log_model,
+    )
+
+
 LOGGER_FACTORY = {
     "dvclive": create_dvclive_logger,
     "csv": create_csv_logger,
     "tensorboard": create_tensorboard_logger,
+    "mlflow": create_mlflow_logger,
 }
 
 
@@ -101,3 +137,4 @@ def build_logger(config: LoggerConfig) -> Logger:
     creation_func = LOGGER_FACTORY[logger_type]
 
     return creation_func(config)
+