It is becoming ever more clear that cities in the future will not be a continuation of the twentieth century's ones. The interdependence of economies, cultures and institutions at both global and local scales; assemblages of infinite numbers of objects and structures; interactions of agents and stakeholders in that physical environment; and information transmissions equally and pervasively through networks show how cities will change and evolve differently. Under this complexity cities could not be explained only by basic production and consumption relations as well as urban planning could not keep pace with planners' desire only by long-term, static and similar land-use decisions. This brings about a new approach towards cities and urban planning. According to this approach cities are assumed to be complex systems, which are dynamic, non-linear, open and evolutionary, adaptive with emerging properties and self-organizing. Since the 1990s research and model studies based on the complexity theory have been accumulated to understand how cities evolve rather than formulating them. With the technological advents in computers and informatics it is possible to identify agents in a city and their relational behaviors while developing scenarios for the future after specifying phase-transitions and bifurcations in the process. By this way complexity in natural sciences could be adapted to social sciences. In this article, we compile prominent computational and mathematical modeling studies such as fractal cities and cellular automata cities in the complexity literature and critical and narrative studies that highlight strategic spatial planning and policy making issues to open new urban planning approach up for discussion.