Neglecting process quality and product quality in software increases development and maintenance costs. Numerous models have been proposed to assess and grade product quality. However, current models mostly require collecting data about the software throughout the process, rely on questionnaires that generate subjective judgments, and include sets of metrics with sharp thresholds. There is an important need to quickly evaluate software that has completed or is about to complete the development phase prior to acceptance testing, and there is a need for a model that produces practical and objective results adapted to the limited data available. In this paper, we review and compare existing software quality assessment models in the literature and industry and propose a new fuzzy logic inference model inspired by them, where only the software code can be used as input. Comparative measurements show that the proposed model provides more stable and realistic results than the Software Improvement Group (SIG) maintainability model, which is one of the modern and practical methods adopted.