The goal of this study was to develop equations to predict CH₄ emissions from beef cattle fed low forage diets (≤20% DM basis) and compare their predictions with IPCC 2006. A dietary forage ≤20% DM database was constructed with treatment means from 17 beef studies published between 2000 and 2014. Criteria for inclusion in the database were: intake, diet composition and enteric CH₄ production. To overcome the limited size of the database (n = 34) each study was resampled 1,000 times using a Monte Carlo technique to create a new virtual data set. Outliers were excluded by Mahalanobis procedure. Three steps were used to obtain new equations: 1) variables associated with CH₄ production were detected by Principal Component Analysis, 2) stepwise forward multiple regression was used with the original database to obtain prediction equations with study included as a random effect using the Mixed procedure, and 3) stepwise forward regression and K-fold cross validation (n = 5) was used with the Monte Carlo data set (n = 34,000). Observed-predicted values were used to evaluate model performance using the concordance correlation (r_c) and root mean square prediction error (RMSPE, g/d). Statistical analysis was performed using JMP v.11. The best-fit equation using the original database was: CH₄ (g/d) = −26.4(±20.17) + 0.21(±0.04) × BW(kg) + 38.1(±11.83) × CP(kg/d) - 70.5(±25.48) × fat²(kg/d) + 10.1(±5.12) × (NDF-ADF)³(kg/d) with P < 0.05, r_c: 0.91 and RMSPE: 13.74; where BW = body weight, CP = crude protein, NDF = neutral detergent fiber, and ADF = acid detergent fiber. The best-fit Monte Carlo equation was: CH₄ (g/d) = −10.1(±0.62) + 0.21(±0.001) × BW(kg) + 0.36(±0.003) × DMI²(kg/d) - 69.2(±1.65) × fat³(kg/d) + 13.0(±0.45) × (CP/NDF) - 4.9(±0.07) × (starch/NDF) with P < 0.001, r_c: 0.92 and RMSPE: 12.6 where DMI = dry matter intake. These new prediction equations had greater r_c and lower RMSPE than IPCC 2006 (r_c:0.29; RMSPE:43.2), indicating greater prediction accuracy. Using the Monte Carlo equation data set improved accuracy of prediction compared with the original equation database. Both equations specifically developed for cattle fed low forage diets increase the accuracy of predicting CH₄ emissions compared with IPCC (2006).