Once you have a fit you can use the predict() function to generate new values. Let's say I have data spanning roughly the range 1 - 3 and I want a prediction at 2.75:
DF <- data.frame(X = c(0.9, 1.1, 2.3, 2.1, 2.9, 3.3),
Y = c(6.7, 6.4, 9.3, 9.8, 12.0, 12.4),
Female = c("M", "F", "M", "F", "M", "F"))
FIT <- lm(Y ~ X + Female, data = DF)
NewDat <- data.frame(X = c(2.75, 2.75), Female = c("M", "F"))
predict(FIT, newdata = NewDat)
#> 1 2
#> 11.20826 11.05944
NewDat$Y <- predict(FIT, newdata = data.frame(X = c(2.75, 2.75), Female = c("M", "F")))
NewDat
#> X Female Y
#> 1 2.75 M 11.20826
#> 2 2.75 F 11.05944
Created on 2019-12-15 by the reprex package (v0.2.1)