This paper refines and extends in fundamental ways an existing model for the numerical assessment of sustainability called sustainability assessment by fuzzy evaluation (SAFE). SAFE, in its basic form, uses fuzzy logic to combine a large suite of basic indicators and then computes numerical values of sustainability for a number of composite indicators such as air, land, economy, health, etc. At a higher hierarchy it computes the sustainability of an ecological and a human component, and finally, it computes overall sustainability of a country or region. As state-of-the-art in fuzzy analysis has advanced, we are prompted to modify SAFE accordingly. The refined model uses the so-called Takagi-Sugeno-Kang inference scheme (TSK) which together with a few technical requirements guarantees monotonicity, i.e., an improvement of a basic indicator leads to an improvement of sustainability. Another refinement concerns the data inputs. To include the effects of past environmental pressures and development policies on the present state of sustainability, we use exponential smoothing to take account of the past with exponentially decaying weights. Finally, the model is now applied to all countries of the world for which data could be obtained and their corresponding sustainabilities are computed. Also, through sensitivity analysis, the most important indicators that affect sustainability are identified.