diff --git a/src/rtichoke/calibration/__init__.py b/src/rtichoke/calibration/__init__.py
index 6e89c060..afcfae45 100644
--- a/src/rtichoke/calibration/__init__.py
+++ b/src/rtichoke/calibration/__init__.py
@@ -2,6 +2,8 @@
 Subpackage for Calibration
 """
 
+import numpy as np
+
 from . import calibration as _calibration
 from ._interactive_aspect import enforce_square_calibration_panel
 
@@ -16,8 +18,35 @@
 ]
 
 
+def _argument(args, kwargs, name, position):
+    return kwargs[name] if name in kwargs else args[position]
+
+
+def _validate_probability_values(probs):
+    for values in probs.values():
+        values = np.asarray(values)
+        if not np.all(np.isfinite(values)) or np.any((values < 0) | (values > 1)):
+            raise ValueError("Estimated probabilities must be between 0 and 1.")
+
+
+def _validate_outcome_values(reals, allowed_values):
+    values = reals.values() if isinstance(reals, dict) else [reals]
+    for outcome_values in values:
+        if not np.all(np.isin(np.asarray(outcome_values), allowed_values)):
+            if allowed_values == (0, 1):
+                raise ValueError("Binary outcomes must contain only 0 and 1.")
+            raise ValueError(
+                "Time-dependent outcomes must contain only 0, 1, and 2."
+            )
+
+
 def create_calibration_curve(*args, **kwargs):
     """Create an interactive calibration plot with a square main panel."""
+    probs = _argument(args, kwargs, "probs", 0)
+    reals = _argument(args, kwargs, "reals", 1)
+    _validate_probability_values(probs)
+    _validate_outcome_values(reals, (0, 1))
+
     return enforce_square_calibration_panel(
         _original_create_calibration_curve(*args, **kwargs)
     )
@@ -25,6 +54,11 @@ def create_calibration_curve(*args, **kwargs):
 
 def create_calibration_curve_times(*args, **kwargs):
     """Create an interactive time-dependent calibration plot with a square main panel."""
+    probs = _argument(args, kwargs, "probs", 0)
+    reals = _argument(args, kwargs, "reals", 1)
+    _validate_probability_values(probs)
+    _validate_outcome_values(reals, (0, 1, 2))
+
     heuristics_sets = kwargs.get("heuristics_sets")
     if heuristics_sets is None:
         heuristics_sets = [dict(_DEFAULT_TIME_CALIBRATION_HEURISTICS[0])]
diff --git a/tests/test_calibration_input_validation.py b/tests/test_calibration_input_validation.py
new file mode 100644
index 00000000..95af28ab
--- /dev/null
+++ b/tests/test_calibration_input_validation.py
@@ -0,0 +1,82 @@
+import numpy as np
+import pytest
+
+from rtichoke import (
+    create_calibration_curve as create_calibration_curve_top_level,
+    create_calibration_curve_times as create_calibration_curve_times_top_level,
+)
+from rtichoke.calibration import (
+    create_calibration_curve,
+    create_calibration_curve_times,
+)
+from rtichoke.calibration.calibration import (
+    create_calibration_curve as create_calibration_curve_direct,
+    create_calibration_curve_times as create_calibration_curve_times_direct,
+)
+
+
+BINARY_ENTRY_POINTS = [
+    create_calibration_curve_top_level,
+    create_calibration_curve,
+    create_calibration_curve_direct,
+]
+TIME_ENTRY_POINTS = [
+    create_calibration_curve_times_top_level,
+    create_calibration_curve_times,
+    create_calibration_curve_times_direct,
+]
+
+
+@pytest.mark.parametrize("entry_point", BINARY_ENTRY_POINTS)
+def test_binary_calibration_rejects_probabilities_outside_unit_interval(entry_point):
+    with pytest.raises(ValueError, match="between 0 and 1"):
+        entry_point(
+            probs={"model": np.array([0.1, 1.1])},
+            reals=np.array([0, 1]),
+        )
+
+
+@pytest.mark.parametrize("entry_point", BINARY_ENTRY_POINTS)
+def test_binary_calibration_rejects_nonbinary_outcomes(entry_point):
+    with pytest.raises(ValueError, match="only 0 and 1"):
+        entry_point(
+            probs={"model": np.array([0.1, 0.9])},
+            reals=np.array([0, 2]),
+        )
+
+
+@pytest.mark.parametrize("entry_point", TIME_ENTRY_POINTS)
+def test_time_calibration_rejects_probabilities_outside_unit_interval(entry_point):
+    with pytest.raises(ValueError, match="between 0 and 1"):
+        entry_point(
+            probs={"model": np.array([-0.1, 0.9])},
+            reals=np.array([0, 1]),
+            times=np.array([1.0, 2.0]),
+            fixed_time_horizons=[1.5],
+        )
+
+
+@pytest.mark.parametrize("entry_point", TIME_ENTRY_POINTS)
+def test_time_calibration_rejects_unsupported_event_codes(entry_point):
+    with pytest.raises(ValueError, match="only 0, 1, and 2"):
+        entry_point(
+            probs={"model": np.array([0.1, 0.9])},
+            reals=np.array([0, 3]),
+            times=np.array([1.0, 2.0]),
+            fixed_time_horizons=[1.5],
+        )
+
+
+def test_calibration_validation_preserves_supported_multiple_population_shape():
+    fig = create_calibration_curve(
+        probs={
+            "population_a": np.array([0.1, 0.8]),
+            "population_b": np.array([0.2, 0.9]),
+        },
+        reals={
+            "population_a": np.array([0, 1]),
+            "population_b": np.array([0, 1]),
+        },
+    )
+
+    assert fig is not None