tCOVID-19 is a new member of the Coronaviridae family that has serious effects on respiratory, gas-trointestinal, and neurological systems. COVID-19 spreads quickly worldwide and affects more than 41.5million persons (till 23 October 2020). It has a high hazard to the safety and health of people all overthe world. COVID-19 has been declared as a global pandemic by the World Health Organization (WHO).Therefore, strict special policies and plans should be made to face this pandemic. Forecasting COVID-19cases in hotspot regions is a critical issue, as it helps the policymakers to develop their future plans. Inthis paper, we propose a new short term forecasting model using an enhanced version of the adaptiveneuro-fuzzy inference system (ANFIS). An improved marine predators algorithm (MPA), called chaoticMPA (CMPA), is applied to enhance the ANFIS and to avoid its shortcomings. More so, we comparedthe proposed CMPA with three artificial intelligence-based models include the original ANFIS, and twomodified versions of ANFIS model using both of the original marine predators algorithm (MPA) and par-ticle swarm optimization (PSO). The forecasting accuracy of the models was compared using differentstatistical assessment criteria. CMPA significantly outperformed all other investigated models.