Technical Abstract: Cows with high persistency tend to produce less milk than expected at the beginning of lactation and more than expected at the end. Best prediction (BP) of persistency is calculated as a function of trait-specific standard lactation curves and linear regressions of test day deviations on days in milk. Because regression coefficients are deviations from a balance point to make yield and persistency phenotypically uncorrelated it should be possible to use 305-d actual yield and persistency to predict yield for lactations with later endpoints. The objectives of this study were to calculate (co)variance components and breeding values for best predictions of persistency of milk (PM), fat (PF), protein (PP), and SCS (PSCS) in breeds other than Holstein, and to demonstrate the calculation of prediction equations for 500-d actual milk yield. Data included lactations from Ayrshire (AY), Brown Swiss (BS), Guernsey (GU), Jersey (JE), and Milking Shorthorn (MS) cows calving since 1997. The number of sires evaluated ranged from 86 (MS) to 3,192 (JE), and mean sire EBV for PM ranged from 0.001 (AY)to 0.10 (BS); mean EBV for PSCS ranged from -0.01 (MS) to -0.043 (JE). Heritabilities were generally highest for PM (0.09 to 0.15) and lowest for PSCS (0.03 to 0.06), with PF and PP having intermediate values (0.07 to 0.13). Repeatabilities varied considerably between breeds, ranging from 0.08 (PSCS in GU, JE, and MS) to 0.28 (PM in GU). Genetic correlations of PM, PF, and PP with PSCS were moderate and favorable, indicating that increasing persistency of SCS is associated with decreases in persistency of yield traits, as expected. Genetic correlations among yield and persistency were low to moderate and ranged from -0.55 (PP, GU) to 0.40 (PP, MS). Prediction equations for 500-d yield were calculated for each breed by regression of 305-d yield and persistency on BP of 500-d yield. Regression coefficients were similar for 305-d yield in all breeds, but those for persistency ranged from 296.86 for BS to 1,059.32 for MS. Goodness-of-fit was very good, with R squared > 0.99 in all cases. Routine genetic evaluations for persistency, as well as the development of prediction equations for several lactation end-points, may provide producers with tools to better manage their herds.