The research is based on the premise that in order for a building energy model to contribute to a sustainable energy future, the model’s accuracy must be ensured in order for the model’s results to be trusted. Therefore, validation processes in continuing Ghanaian building performance studies are outlined. The process started with long-term monitoring of low-rise, multi-storey and test cells structures. Combined with weather data from meteorological offices, reliance on synthetic weather files and local measurements, appropriate matching periods of weather data and measurements were used to simulate indoor parameters. Further, the simulated and measured data were in good agreement in terms of regression values (r2of 0.53–0.96). Energy use bills were used to validate energy loads of a multi-story building which resulted in a difference of 0.09% between the simulated and billed data. Furthermore, an approach of using the Coefficient of Variance for Root Mean Square Error (CV (RMSE)) was also presented. Considering the range of the regression values which could be due to the difficulty in the validating process; one can confidently rely on the outcome to predict building performance. Sampled challenges are the potential of synthetic weather files to overlook microclimatic conditions such as urban heat island effects; difficulty in predicting internal loads as comprehensive monitoring devices are lacking, e.g., occupancy sensors to monitor the actual number of people present at a time and their behaviour within spaces; system performance values which are known to decline with time, therefore, affecting measured versus simulated values; most firms not keeping energy bills and their unwillingness to provide the information to researchers; etc. The validated models can be used as scientific-based data and analysis to inform building designers decisions to reduce the economic and environmental burden in Ghana.