## Summary

The objectives of the present paper were to develop and evaluate empirical equations to predict fractional passage rate (kp) of forages commonly fed to goats using chemical composition of the diet and animal information. Two databases were created. The first (development database) was assembled from four studies that had individual information on animals, diets and faecal marker concentrations over time (up to 120 h post-feeding); it contained 54 data points obtained from Latin square designs. The second (evaluation database) was built using published information gathered from the literature. The evaluation database was comprised of five studies, containing 39 data points on diverse types of diets and animal breeds. The kp was estimated using a time-dependent model based on the Gamma distribution with at least two and up to 12 (rumen)+one (post-rumen) compartments (i.e. G2G1–G12G1) developed from the development database. Statistical analyses were carried out using standard regression analysis and random coefficient model analysis to account for random sources (i.e. study). The evaluation of the developed empirical equation was conducted using regression analysis adjusted for study effects, concordance correlation coefficient and mean square error of prediction. Sensitivity analyses with the developed empirical equation and comparable published equations were performed using Monte Carlo simulations. The G2G1 model consistently had lower sum of squares of errors and greater relative likelihood probabilities than other GnG1 versions. The kp was influenced by several dietary nutrients, including dietary concentration or intake of components such as lignin, neutral detergent fibre (NDF), hemicellulose, crude protein (CP), acid detergent fibre (ADF) and animal body weight (BW). The selected empirical equation, adjusted for study effects, () had an R2 of 0·623 and root of mean square error (RMSE) of 0·0122/h. The evaluation of the adequacy of the selected equation with the evaluation database indicated no systematic bias (slope not different from 1), but a low accuracy (0·33) and a persistent mean bias of 0·0129/h. The sensitivity analysis indicated that the selected empirical equation was most sensitive to changes in dry matter intake (DMI, kg/d), BW(kg) and NDF (g/kg dry matter) with standardized regression coefficients of 0·98, −0·43 and −0·32, respectively. The sensitivity analysis also indicated that the greatest forage kp in goats is likely to be c. 0·0569/h. The comparison with a previously published empirical equation containing data on cattle, sheep and goats, suggested that the distribution of the present empirical equation, adjusted for mean bias, is wider and that kp of goats might be similar to cattle and sheep when fed high amounts of forage under confinement conditions.