ABSTRACT Colombia, like many developing nations, does not have a strong health system able to respond to a pandemic of the magnitude of Covid-19. There is an increasing need to create a model that allows particular clinics and hospitals to estimate the number of patients that require Intensive Care Units-ICU care (critical), and the number of patients that require hospital care (severe), but not ICU care, in order to manage their limited resources. This paper presents a prediction of the total number of ICU and regular beds that will be needed during the pandemic COVID-19 for Bogotá-Colombia. We use a SEIR model that includes three different compartments of infection: those who can stay at home, those in regular hospital beds and those in need of ICU treatment. The model allows for a time varying transmission rate which we use to incorporate the measures introduced by the government over the period of one semester. The model predicts that by mid October 2020, the city will need 4 524 prevalent ICUs needed and 16 738 regular hospital beds needed. By the third week of July 2020, the number of patients that need ICUs will overpass the capacity set at 1 200 beds for ICU hospital beds in the city. The model predicts that the death toll by the same date will reach 1 752 people and the number of cases will be 30 216 inhabitants by then. We provide a Shiny app available in https://claudia-rivera-rodriguez.shinyapps.io/shinyappcovidclinic/ . The original values in the app reproduce the results of this paper, but the parameters and starting values can be changed according to the users needs. COVID-19 has posed too many challenges to health systems around the globe, this model is an useful tool for cities, hospitals and clinics in Colombia that need to prepare for the excess demand of services that a pandemic like this one generates. Unfortunately, the model predicts that by the third week of July the projected capacity of the system in Bogotá will not be enough. We expect the lockdown rules strength in the future days, so the death toll is not as bad as predicted by this model.