diff --git a/api/app/models/metrics/model_quality_dto.py b/api/app/models/metrics/model_quality_dto.py
index 965c107a..b95d3844 100644
--- a/api/app/models/metrics/model_quality_dto.py
+++ b/api/app/models/metrics/model_quality_dto.py
@@ -125,14 +125,25 @@ class CurrentMultiClassificationModelQuality(BaseModel):
     model_config = ConfigDict(populate_by_name=True, alias_generator=to_camel)
 
 
-class RegressionMetricsBase(BaseModel):
-    r2: Optional[float] = None
-    mae: Optional[float] = None
-    mse: Optional[float] = None
-    variance: Optional[float] = None
-    mape: Optional[float] = None
-    rmse: Optional[float] = None
-    adj_r2: Optional[float] = None
+class KsMetrics(BaseModel):
+    p_value: Optional[float] = None
+    statistic: Optional[float] = None
+
+    model_config = ConfigDict(populate_by_name=True, alias_generator=to_camel)
+
+
+class Histogram(BaseModel):
+    buckets: List[float]
+    values: Optional[List[int]] = None
+
+
+class ResidualsMetrics(BaseModel):
+    ks: KsMetrics
+    correlation_coefficient: Optional[float] = None
+    histogram: Histogram
+    standardized_residuals: List[float]
+    predictions: List[float]
+    targets: List[float]
 
     model_config = ConfigDict(populate_by_name=True, alias_generator=to_camel)
 
@@ -145,6 +156,7 @@ class BaseRegressionMetrics(BaseModel):
     mape: Optional[float] = None
     rmse: Optional[float] = None
     adj_r2: Optional[float] = None
+    residuals: ResidualsMetrics
 
     model_config = ConfigDict(populate_by_name=True, alias_generator=to_camel)
 
diff --git a/api/tests/commons/db_mock.py b/api/tests/commons/db_mock.py
index 717b9612..fcf66dfe 100644
--- a/api/tests/commons/db_mock.py
+++ b/api/tests/commons/db_mock.py
@@ -324,6 +324,20 @@ def get_sample_current_dataset(
     'rmse': 202.23194752188695,
     'adj_r2': 0.9116805380966796,
     'variance': 0.23,
+    'residuals': {
+        'ks': {
+            'p_value': 0.01,
+            'statistic': 0.4,
+        },
+        'histogram': {
+            'values': [1, 2, 3],
+            'buckets': [-3.2, -1, 2.2],
+        },
+        'correlation_coefficient': 0.01,
+        'standardized_residuals': [0.02, 0.03],
+        'targets': [1, 2.2, 3],
+        'predictions': [1.3, 2, 4.5],
+    },
 }
 
 grouped_regression_model_quality_dict = {
diff --git a/sdk/radicalbit_platform_sdk/models/dataset_model_quality.py b/sdk/radicalbit_platform_sdk/models/dataset_model_quality.py
index 258c10e2..362a3404 100644
--- a/sdk/radicalbit_platform_sdk/models/dataset_model_quality.py
+++ b/sdk/radicalbit_platform_sdk/models/dataset_model_quality.py
@@ -124,6 +124,29 @@ class CurrentMultiClassificationModelQuality(ModelQuality):
     model_config = ConfigDict(populate_by_name=True, alias_generator=to_camel)
 
 
+class KsMetrics(BaseModel):
+    p_value: Optional[float] = None
+    statistic: Optional[float] = None
+
+    model_config = ConfigDict(populate_by_name=True, alias_generator=to_camel)
+
+
+class Histogram(BaseModel):
+    buckets: List[float]
+    values: Optional[List[int]] = None
+
+
+class ResidualsMetrics(BaseModel):
+    ks: KsMetrics
+    correlation_coefficient: Optional[float] = None
+    histogram: Histogram
+    standardized_residuals: List[float]
+    predictions: List[float]
+    targets: List[float]
+
+    model_config = ConfigDict(populate_by_name=True, alias_generator=to_camel)
+
+
 class BaseRegressionMetrics(BaseModel):
     r2: Optional[float] = None
     mae: Optional[float] = None
@@ -132,6 +155,7 @@ class BaseRegressionMetrics(BaseModel):
     mape: Optional[float] = None
     rmse: Optional[float] = None
     adj_r2: Optional[float] = None
+    residuals: ResidualsMetrics
 
     model_config = ConfigDict(populate_by_name=True, alias_generator=to_camel)
 
diff --git a/sdk/tests/apis/model_current_dataset_test.py b/sdk/tests/apis/model_current_dataset_test.py
index 28e6b4fb..b469058f 100644
--- a/sdk/tests/apis/model_current_dataset_test.py
+++ b/sdk/tests/apis/model_current_dataset_test.py
@@ -958,6 +958,9 @@ def test_regression_model_quality_ok(self):
         mape = 35.19
         rmse = 202.23
         adj_r2 = 0.91
+        p_value = 0.2
+        statistic = 0.4
+        correlation_coefficient = 0.2
         model_current_dataset = ModelCurrentDataset(
             base_url,
             model_id,
@@ -986,7 +989,21 @@ def test_regression_model_quality_ok(self):
                             "variance": {variance},
                             "mape": {mape},
                             "rmse": {rmse},
-                            "adjR2": {adj_r2}
+                            "adjR2": {adj_r2},
+                            "residuals": {{
+                                "ks": {{
+                                    "p_value": {p_value},
+                                    "statistic": {statistic}
+                                }},
+                                "histogram": {{
+                                    "values": [1, 2, 3],
+                                    "buckets": [-3.2, -1, 2.2]
+                                }},
+                                "correlationCoefficient": {correlation_coefficient},
+                                "standardizedResiduals": [0.02, 0.03],
+                                "targets": [1, 2.2, 3],
+                                "predictions": [1.3, 2, 4.5]
+                            }}
                         }},
                         "grouped_metrics": {{
                             "r2": [
@@ -1032,6 +1049,12 @@ def test_regression_model_quality_ok(self):
         assert metrics.global_metrics.mape == mape
         assert metrics.global_metrics.rmse == rmse
         assert metrics.global_metrics.adj_r2 == adj_r2
+        assert (
+            metrics.global_metrics.residuals.correlation_coefficient
+            == correlation_coefficient
+        )
+        assert metrics.global_metrics.residuals.ks.p_value == p_value
+        assert metrics.global_metrics.residuals.ks.statistic == statistic
         assert metrics.grouped_metrics.r2[0].value == r2
         assert metrics.grouped_metrics.mae[0].value == mae
         assert metrics.grouped_metrics.mse[0].value == mse
diff --git a/sdk/tests/apis/model_reference_dataset_test.py b/sdk/tests/apis/model_reference_dataset_test.py
index ac1605e9..e367b97b 100644
--- a/sdk/tests/apis/model_reference_dataset_test.py
+++ b/sdk/tests/apis/model_reference_dataset_test.py
@@ -349,6 +349,9 @@ def test_regression_model_metrics_ok(self):
         mape = 35.19
         rmse = 202.23
         adj_r2 = 0.91
+        p_value = 0.2
+        statistic = 0.4
+        correlation_coefficient = 0.2
         model_reference_dataset = ModelReferenceDataset(
             base_url,
             model_id,
@@ -375,7 +378,21 @@ def test_regression_model_metrics_ok(self):
                         "variance": {variance},
                         "mape": {mape},
                         "rmse": {rmse},
-                        "adjR2": {adj_r2}
+                        "adjR2": {adj_r2},
+                        "residuals": {{
+                            "ks": {{
+                                "p_value": {p_value},
+                                "statistic": {statistic}
+                            }},
+                            "histogram": {{
+                                "values": [1, 2, 3],
+                                "buckets": [-3.2, -1, 2.2]
+                            }},
+                            "correlationCoefficient": {correlation_coefficient},
+                            "standardizedResiduals": [0.02, 0.03],
+                            "targets": [1, 2.2, 3],
+                            "predictions": [1.3, 2, 4.5]
+                        }}
                     }}
                 }}""",
         )
@@ -390,6 +407,9 @@ def test_regression_model_metrics_ok(self):
         assert metrics.mape == mape
         assert metrics.rmse == rmse
         assert metrics.adj_r2 == adj_r2
+        assert metrics.residuals.correlation_coefficient == correlation_coefficient
+        assert metrics.residuals.ks.p_value == p_value
+        assert metrics.residuals.ks.statistic == statistic
         assert model_reference_dataset.status() == JobStatus.SUCCEEDED
 
     @responses.activate