The COVID-19 pandemic necessitates forecasts to frame science-informed policies. An accurate forecast of the size and timing of future waves could help public health officials and governments to plan appropriate responses. An ensemble forecast by aggregating different scenarios and models makes the prediction robust and reliable. We present an ensemble forecast for Wave-3 of COVID-19 in the state of Karnataka, India, using the IISc Population Balance Model for infectious disease spread. The reported data of confirmed, recovered, and deceased cases in Karnataka from 1 July 2020 to 4 July 2021 are utilized to tune the model’s parameters. An ensemble forecast is done from 5 July 2021 to 30 June 2022. The ensemble is built with 972 members by varying seven critical parameters that quantify the uncertainty in the spread dynamics (antibody waning, viral mutation) and interventions (pharmaceutical, non-pharmaceutical). The probability of Wave-3, the peak date distribution, and the peak caseload distribution are estimated from the ensemble forecast. Analysis of the ensemble forecast results shows that compliance to COVID-appropriate behaviour, daily vaccination rate, and emergence time of immune-escape new variants are the most significant causal factors that determine the timing and severity of COVID-19 Wave-3. We observe that when compliance to COVID-appropriate behaviour is similar to a lockdown-like situation, the emergence of new immune-escape variants beyond September 2021 is unlikely to induce a new wave. No or partial compliance to COVID-appropriate behaviour makes a new wave inevitable. However, increasing the vaccination rate reduces the active caseload at Wave-3’s peak. If Wave-3 emerges, on average, the daily confirmed caseload of children (Age 0–17 years) could be up to seven times more than the corresponding caseload (4390) at Wave-2’s peak. Therefore, large-scale surveillance, including genome sequencing for early detection of new variants and non-pharmaceutical interventions to improve COVID-Appropriate behaviour, is vital to prevent Wave-3 of COVID-19. Doubling the vaccination rate as of 4 July 2021 to 560K doses per day will reduce the daily confirmed cases even if Wave-3 arises. Consequently, hospitalizations, ICU, and Oxygen requirements can be decreased. Since vaccination is yet to start in children, it is essential to ramp up the public health facilities, including pediatric ICUs to treat MIS-C, by 5-9 times to handle the worst-case situation. From a modeling perspective, capturing the nonlinear dynamics induced by the uncertainties in the causal factors is the key to a successful forecast. Therefore, an effort should be made to build an ensemble forecast that contains multiple models and, more importantly, models that account for causal factor uncertainties.