diff --git a/caimira/apps/calculator/__init__.py b/caimira/apps/calculator/__init__.py
index ea869fec..1ce280fe 100644
--- a/caimira/apps/calculator/__init__.py
+++ b/caimira/apps/calculator/__init__.py
@@ -386,21 +386,33 @@ class CO2Data(BaseRequestHandler):
             result_set.add(times[CO2_values.index(max(CO2_np[segment]))])
         return list(result_set)
 
-    def generate_ventilation_plot(self, CO2_data: dict, transition_times: typing.Optional[list] = None, ventilation_values: typing.Optional[list] = None):
+    def generate_ventilation_plot(self, CO2_data: dict, 
+                                  transition_times: typing.Optional[list] = None, 
+                                  ventilation_values: typing.Optional[list] = None,
+                                  predictive_CO2: typing.Optional[list] = None):
             times = CO2_data['times']
             CO2_data = CO2_data['CO2']
 
+            def time_to_hour(time: float) -> str:
+                minutes = int(np.floor((time % 1) * 60))
+                minutes_to_display = f'0{minutes}' if minutes < 10 else minutes
+                return f'{int(np.floor(time))}:{minutes_to_display}'
+
             fig = plt.figure(figsize=(7, 4), dpi=110)
-            plt.plot(times, CO2_data)
+            plt.plot(times, CO2_data, label='Input CO₂')
 
             if (transition_times):
                 for index, time in enumerate(transition_times):
                     plt.axvline(x = time, color = 'grey', linewidth=0.5, linestyle='--')
+                    plt.text(x = time + 0.04, y = max(predictive_CO2) if predictive_CO2 else max(CO2_data), s=time_to_hour(time))
                     if ventilation_values:
                         y_location = (CO2_data[min(range(len(times)), key=lambda i: abs(times[i]-time))])
                         plt.text(x = time + 0.04, y = y_location, s="{:.2g}".format(ventilation_values[index]))
+            if (predictive_CO2):
+                plt.plot(times, predictive_CO2, label='Predictive CO₂')
             plt.xlabel('Time of day')
             plt.ylabel('Concentration (ppm)')
+            plt.legend(loc='lower right')
             return img2base64(_figure2bytes(fig))
     
     async def post(self, endpoint: str) -> None:
@@ -431,9 +443,14 @@ class CO2Data(BaseRequestHandler):
             report = await asyncio.wrap_future(report_task)
         
             result = dict(report.CO2_fit_params())
+            ventilation_transition_times = report.ventilation_transition_times
+
             result['fitting_ventilation_type'] = form.fitting_ventilation_type
-            result['transition_times'] = report.ventilation_transition_times
-            result['CO2_plot'] = self.generate_ventilation_plot(form.CO2_data, report.ventilation_transition_times[:-1], result['ventilation_values'])
+            result['transition_times'] = ventilation_transition_times
+            result['CO2_plot'] = self.generate_ventilation_plot(form.CO2_data, 
+                                                                ventilation_transition_times[:-1], 
+                                                                result['ventilation_values'],
+                                                                result['predictive_CO2'])
             self.finish(result)
         
 
diff --git a/caimira/models.py b/caimira/models.py
index 2f04a0bb..4da916ce 100644
--- a/caimira/models.py
+++ b/caimira/models.py
@@ -1540,8 +1540,8 @@ class CO2DataModel:
 
         exhalation_rate = res_dict['x'][0]
         ventilation_values = res_dict['x'][1:]
-
-        return {"exhalation_rate": exhalation_rate, "ventilation_values": list(ventilation_values)}
+        predictive_CO2 = self.CO2_concentrations_from_params(exhalation_rate=exhalation_rate, ventilation_values=ventilation_values)
+        return {"exhalation_rate": exhalation_rate, "ventilation_values": list(ventilation_values), 'predictive_CO2': list(predictive_CO2)}
 
 
 @dataclass(frozen=True)