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Small cities in developing countries are under a set of transitions that imperil their sustainability and whose repercussions can reach the international level. Therefore, local decision-makers need specific geoprospective urban models to seek alternative pathways. This paper presents a housing allocation model, designed to meet the context of small cities in developing countries. It is a multi-level Cellular Automata that relies on a new apprehension of urbanisation process, implemented through raster irregular grid with time-step variation. The model application to reconstruct housing dynamics in Kasba-Tadla city in Morocco, between 1999 and 2016, confirmed its ability to mimic well the spatio-temporal allocation of housing settlements. The obtained results showed that the spatial allocation of informal settlements is not anarchic, but driven by flexible rules, and also revealed Kasba-Tadla city could have better negotiated the after ‘Arab Spring’ urban transformations if local decision-makers had foreknowledge. [ABSTRACT FROM AUTHOR]