This paper explains a predictive model developed by using multiple linear regression techniques: 38 factors were regressed against two dependent variables, satisfaction with (a) the quality of life in the Flint area, and (b) the quality of life in the neighborhood. The 38 independent factors used in the modeling represented various social and psychological aspects of community life. Among the major predictors of community-wide satisfaction were Trust in Government and Political System, satisfaction with Family and Friends, Aesthetic Quality of the Community, and Age and Years in Community, and Optimism about the Community. Important predictors of satisfaction with neighborhood quality were satisfaction with Neighbors, Home, and Aesthetic Quality of the Community. In order to save or restore any kind of major human system, decision- and policy-makers need appropriate and reliable information about conditions within the system. They also need to possess an awareness of the relationship existing among the multitude of components constituting that system. Relative to American cities today, neither adequate data nor knowledge of relationship exists. What is needed is a general systems model which explains the economic, political, social, psychological, and environmental factors that make cities what they are. This is a tremendously tall order, but one that should gain support from every student of urban systems. To tackle the whole challenge laid out above is not the scope of this study. The purpose is to explore a little
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