Abstract: A computer implemented method for predictive modeling, which includes collecting data relating to properties leased to tenants, including features relating to the properties, the tenants, regional data, national data, or global data. Additional features are derived from the collected data, including additional features relating to the properties or the tenants. Each of the properties of the tenants is labeled to indicate a characteristic of the property or the tenant, where each labeled property or tenant is associated with property-features or tenant-features. A machine-learning based model is trained to predict a parameter a specific property or of a specific tenant, using a first subset of the labeled data. Following the training, and in response to receipt of an indication of a specific property or tenant, a prediction of the parameter for the property or the tenant is obtained from the machine-learning based model, and a report including the prediction is generated.