diff --git a/examples/binary_classification/Main.hs b/examples/binary_classification/Main.hs
index b6add3a..90db014 100644
--- a/examples/binary_classification/Main.hs
+++ b/examples/binary_classification/Main.hs
@@ -47,7 +47,9 @@ main = do
           LGBM.trainNewModel modelName trainParams trainingData testData 100
         case model of
           Left e -> print e
-          Right m -> LGBM.predict m testData predictionFile
+          Right m -> do
+            _ <- LGBM.predict m testData predictionFile
+            return ()
 
         modelB <- fileDiff modelName "golden_model.txt"
         modelP <- fileDiff predictionFile "golden_prediction.txt"
diff --git a/examples/lambdarank/Main.hs b/examples/lambdarank/Main.hs
index e439016..48f3b1f 100644
--- a/examples/lambdarank/Main.hs
+++ b/examples/lambdarank/Main.hs
@@ -46,7 +46,9 @@ main = do
 
         case model of
           Left e -> print e
-          Right m -> LGBM.predict m testData predictionFile
+          Right m -> do
+            _ <- LGBM.predict m testData predictionFile
+            return ()
 
         modelB <- fileDiff modelName "golden_model.txt"
         modelP <- fileDiff predictionFile "golden_prediction.txt"
diff --git a/examples/multiclass_classification/Main.hs b/examples/multiclass_classification/Main.hs
index 087a5ac..210a1f3 100644
--- a/examples/multiclass_classification/Main.hs
+++ b/examples/multiclass_classification/Main.hs
@@ -40,7 +40,9 @@ main = do
           LGBM.trainNewModel modelName trainParams trainingData testData 100
         case model of
           Left e -> print e
-          Right m -> LGBM.predict m testData predictionFile
+          Right m -> do
+            _ <- LGBM.predict m testData predictionFile
+            return ()
 
         modelB <- fileDiff modelName "golden_model.txt"
         modelP <- fileDiff predictionFile "golden_prediction.txt"
diff --git a/examples/regression/Main.hs b/examples/regression/Main.hs
index eaea800..fe3b70d 100644
--- a/examples/regression/Main.hs
+++ b/examples/regression/Main.hs
@@ -45,7 +45,9 @@ main = do
           LGBM.trainNewModel modelName trainParams trainingData testData 100
         case model of
           Left e -> print e
-          Right m -> LGBM.predict m testData predictionFile
+          Right m -> do
+            _ <- LGBM.predict m testData predictionFile
+            return ()
 
         modelB <- fileDiff modelName "golden_model.txt"
         modelP <- fileDiff predictionFile "golden_prediction.txt"
diff --git a/examples/titanic/Main.hs b/examples/titanic/Main.hs
index 4f6beee..3801d9c 100644
--- a/examples/titanic/Main.hs
+++ b/examples/titanic/Main.hs
@@ -69,9 +69,8 @@ trainModel =
         Right m -> do
           print $ "Model trained and saved to file:  " ++ modelName
 
-          LGBM.predict m validationData predictionFile
-          predictions <-
-            map read . lines <$> readFile predictionFile :: IO [Double]
+          predictionSet <- LGBM.predict m validationData predictionFile
+          predictions <- LGBM.dsToList predictionSet :: IO [Double]
           valData <- BSL.readFile valFile
           let knowns = V.toList $ readColumn 0 CSV.HasHeader valData :: [Int]
           print $ "Self Accuracy:  " ++ show (accuracy (round <$> predictions) knowns :: Double)
@@ -91,7 +90,7 @@ main = do
           hClose testHandle
           TMP.withSystemTempFile "predictions" $ \predFile predHandle -> do
             hClose predHandle
-            LGBM.predict m (loadData testFile) predFile
+            _ <- LGBM.predict m (loadData testFile) predFile
 
             withFile "TitanicSubmission.csv" WriteMode $ \submHandle -> do
               testBytes <- BSL.readFile testFile
diff --git a/src/LightGBM.hs b/src/LightGBM.hs
index 073f3dc..aba146b 100644
--- a/src/LightGBM.hs
+++ b/src/LightGBM.hs
@@ -44,6 +44,7 @@ module LightGBM
     loadDataFromFile
   , DataSet
   , HasHeader(..)
+  , dsToList
     -- * Models
   , Model
   , trainNewModel
@@ -85,6 +86,10 @@ newtype HasHeader = HasHeader
 loadDataFromFile :: HasHeader -> FilePath -> DataSet
 loadDataFromFile = flip DataSet
 
+-- | Convert a DataSet into a list of records for whatever type is relevant.
+dsToList :: Read a => DataSet -> IO [a]
+dsToList ds =  map read . lines <$> readFile (dataPath ds)
+
 -- | A model to use to make predictions
 data Model = Model
   { modelPath :: FilePath
@@ -117,18 +122,13 @@ trainNewModel modelOutputPath trainingParams trainingData validationData numRoun
 loadModelFromFile :: FilePath -> Model
 loadModelFromFile = Model
 
--- FIXME:
---  - we might want to return the predictions in a better form
---    than just the file...
---  - Duplication of the exec path between predict and
---    train. Use a Reader monad maybe?
 -- | Predict the results of new inputs and persist the results to an
 -- output file.
 predict ::
      Model -- ^ A model to do prediction with
   -> DataSet -- ^ The new input data for prediction
   -> FilePath -- ^ Where to persist the prediction outputs
-  -> IO ()
+  -> IO DataSet -- ^ The prediction output DataSet
 predict model inputData predictionOutputPath = do
   let dataParams = [P.HasHeader (getHeader . hasHeader $ inputData)]
       runParams =
@@ -138,4 +138,4 @@ predict model inputData predictionOutputPath = do
         , P.OutputResult predictionOutputPath
         ]
   _ <- CLW.run lightgbmExe $ concat [dataParams, runParams]
-  return ()
+  return $ DataSet predictionOutputPath (HasHeader False)