In estimating the performance of parallel microchannels, non-uniformity of flow distribution (φ) and pressure drop (p) are critical parameters. These parameters are affected by flow rate, the inlet flow configuration and microchip geometric factors. This paper, in a constant rate, and configuration of fluid entrance into the chip, examines the effect of geometric—channels and manifolds—parameters on φ and p. For this purpose, by employing a set of CFD models modeled in COMSOL, a finite element software, the effect of each geometric factor is examined separately. The results show that increasing the number of channels, the distance between channels, the concavity, and reducing the width of the channel has a positive effect on the distribution of flow between the channels. Moreover, reducing the convexity, increasing the number of channels, increasing the distance between channels, and declining the width of the channels leads to an increase in p. Eventually, a hybrid artificial neural network (MLP-ICA) is trained by means of 245 CFD models to derive the model of changing of φ and p with the geometric parameters. The MLP-ICA predictive model of φ the R2 of 0.9912 and the MSE of 4.1 × 10–4 demonstrate the higher accuracy of this model than MLP Model with R2 of 0.9466 MSE of 7.9 × 10–3.
