diff --git a/qiskit_ibm_runtime/utils/runner_result.py b/qiskit_ibm_runtime/utils/runner_result.py
new file mode 100644
index 000000000..7db4f1989
--- /dev/null
+++ b/qiskit_ibm_runtime/utils/runner_result.py
@@ -0,0 +1,74 @@
+# This code is part of Qiskit.
+#
+# (C) Copyright IBM 2021.
+#
+# This code is licensed under the Apache License, Version 2.0. You may
+# obtain a copy of this license in the LICENSE.txt file in the root directory
+# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
+#
+# Any modifications or derivative works of this code must retain this
+# copyright notice, and modified files need to carry a notice indicating
+# that they have been altered from the originals.
+
+"""Circuit-runner result class"""
+
+from typing import List, Union
+import json
+
+from qiskit.result import Result, QuasiDistribution
+from qiskit.result.postprocess import _hex_to_bin
+from qiskit.exceptions import QiskitError
+
+from ..program import ResultDecoder
+
+
+class RunnerResult(Result, ResultDecoder):
+    """Result class for Qiskit Runtime program circuit-runner."""
+
+    @classmethod
+    def decode(cls, data: str) -> "RunnerResult":
+        """Decoding for results from Qiskit runtime jobs."""
+        return cls.from_dict(json.loads(data))
+
+    def get_quasiprobabilities(
+        self, experiment: Union[int, List] = None
+    ) -> Union[QuasiDistribution, List[QuasiDistribution]]:
+        """Get quasiprobabilites associated with one or more experiments.
+
+        Parameters:
+            experiment: Indices of experiments to grab quasiprobabilities from.
+
+        Returns:
+            A single distribution or a list of distributions.
+
+        Raises:
+            QiskitError: If experiment result doesn't contain quasiprobabilities.
+        """
+        if experiment is None:
+            exp_keys = range(len(self.results))
+        else:
+            exp_keys = [experiment]  # type: ignore[assignment]
+
+        dict_list = []
+        for key in exp_keys:
+            if "quasiprobabilities" in self.data(key).keys():
+                shots = self.results[key].shots
+                hex_quasi = self.results[key].data.quasiprobabilities
+                bit_lenth = len(self.results[key].header.final_measurement_mapping)
+                quasi = {}
+                for hkey, val in hex_quasi.items():
+                    quasi[_hex_to_bin(hkey).zfill(bit_lenth)] = val
+
+                out = QuasiDistribution(quasi, shots)
+                out.shots = shots
+                dict_list.append(out)
+            else:
+                raise QiskitError(
+                    'No quasiprobabilities for experiment "{}"'.format(repr(key))
+                )
+
+        # Return first item of dict_list if size is 1
+        if len(dict_list) == 1:
+            return dict_list[0]
+        else:
+            return dict_list