diff --git a/CHANGELOG.md b/CHANGELOG.md
index 5990242..3c44b94 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -9,6 +9,7 @@ This changelog references the relevant changes done in PHP-ML library.
     * feature [Dataset] added removeColumns function to ArrayDataset (#249)
     * feature [Dataset] added a SvmDataset class for SVM-Light (or LibSVM) format files (#237)
     * feature [Optimizer] removed $initialTheta property and renamed setInitialTheta method to setTheta (#252)
+    * change [Imputer] Throw exception when trying to transform without train data (#314)
     * enhancement Add performance test for LeastSquares (#263)
     * enhancement Micro optimization for matrix multiplication (#255)
     * enhancement Throw proper exception (#259, #251)
diff --git a/docs/machine-learning/preprocessing/imputation-missing-values.md b/docs/machine-learning/preprocessing/imputation-missing-values.md
index 48a5b3a..219db22 100644
--- a/docs/machine-learning/preprocessing/imputation-missing-values.md
+++ b/docs/machine-learning/preprocessing/imputation-missing-values.md
@@ -8,6 +8,7 @@ To solve this problem you can use the `Imputer` class.
 * $missingValue (mixed) - this value will be replaced (default null)
 * $strategy (Strategy) - imputation strategy (read to use: MeanStrategy, MedianStrategy, MostFrequentStrategy)
 * $axis (int) - axis for strategy, Imputer::AXIS_COLUMN or Imputer::AXIS_ROW
+* $samples (array) - array of samples to train
 
 ```
 $imputer = new Imputer(null, new MeanStrategy(), Imputer::AXIS_COLUMN);
@@ -34,6 +35,7 @@ $data = [
 ];
 
 $imputer = new Imputer(null, new MeanStrategy(), Imputer::AXIS_COLUMN);
+$imputer->fit($data);
 $imputer->transform($data);
 
 /*
@@ -46,3 +48,20 @@ $data = [
 */
 
 ```
+
+You can also use `$samples` constructer parameter instead of `fit` method:
+
+```
+use Phpml\Preprocessing\Imputer;
+use Phpml\Preprocessing\Imputer\Strategy\MeanStrategy;
+
+$data = [
+    [1, null, 3, 4],
+    [4, 3, 2, 1],
+    [null, 6, 7, 8],
+    [8, 7, null, 5],
+];
+
+$imputer = new Imputer(null, new MeanStrategy(), Imputer::AXIS_COLUMN, $data);
+$imputer->transform($data);
+```
diff --git a/src/Preprocessing/Imputer.php b/src/Preprocessing/Imputer.php
index fdce666..e5b5af8 100644
--- a/src/Preprocessing/Imputer.php
+++ b/src/Preprocessing/Imputer.php
@@ -4,6 +4,7 @@ declare(strict_types=1);
 
 namespace Phpml\Preprocessing;
 
+use Phpml\Exception\InvalidOperationException;
 use Phpml\Preprocessing\Imputer\Strategy;
 
 class Imputer implements Preprocessor
@@ -50,6 +51,10 @@ class Imputer implements Preprocessor
 
     public function transform(array &$samples): void
     {
+        if ($this->samples === []) {
+            throw new InvalidOperationException('Missing training samples for Imputer.');
+        }
+
         foreach ($samples as &$sample) {
             $this->preprocessSample($sample);
         }
diff --git a/tests/Preprocessing/ImputerTest.php b/tests/Preprocessing/ImputerTest.php
index c229c15..1078e54 100644
--- a/tests/Preprocessing/ImputerTest.php
+++ b/tests/Preprocessing/ImputerTest.php
@@ -4,6 +4,7 @@ declare(strict_types=1);
 
 namespace Phpml\Tests\Preprocessing;
 
+use Phpml\Exception\InvalidOperationException;
 use Phpml\Preprocessing\Imputer;
 use Phpml\Preprocessing\Imputer\Strategy\MeanStrategy;
 use Phpml\Preprocessing\Imputer\Strategy\MedianStrategy;
@@ -173,4 +174,18 @@ class ImputerTest extends TestCase
 
         $this->assertEquals($imputeData, $data, '', $delta = 0.01);
     }
+
+    public function testThrowExceptionWhenTryingToTransformWithoutTrainSamples(): void
+    {
+        $this->expectException(InvalidOperationException::class);
+
+        $data = [
+            [1, 3, null],
+            [6, null, 8],
+            [null, 7, 5],
+        ];
+
+        $imputer = new Imputer(null, new MeanStrategy(), Imputer::AXIS_COLUMN);
+        $imputer->transform($data);
+    }
 }