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This study provides a simple model for biomass char yield obtained under conditions relevant for suspension ring. Using the multivariate data analysis methods, principal component analysis (PCA) and partial least squares regression (PLS regression), an equation is presented, which predict the char yield for wood and herbaceous biomass. The model parameters are heating rate (0.1-12 •10 3 K/s), average particle size (0.13-0.93 mm), maximum temperature (873-1673 K), potassium content (from 0.02 wt% db and upwards), and char yield (1-15 wt% daf). The model is developed based on wood biomass data and subsequently expanded to include straw and other herbaceous biomass. It is validated against experimental data from the literature and in general it exhibits the same characteristics. Independent data sets of wood are predicted with an average error (RMSEP) of 0.9 wt%point daf, and straw with an RMSEP = 0.9 wt% daf for the model, when a slope/intercept correction is applied, or RMSEP = 1.1 wt% daf otherwise. To include herbaceous biomass, the model introduces a potassium cut o level at 0.53wt%db, because the catalytic eect of potassium on the devolatilization 1