diff --git a/docs/src/user/api.md b/docs/src/user/api.md
index 25289ed7..fe19c434 100644
--- a/docs/src/user/api.md
+++ b/docs/src/user/api.md
@@ -9,6 +9,8 @@ CurrentModule = ForwardDiff
 ```@docs
 ForwardDiff.derivative
 ForwardDiff.derivative!
+ForwardDiff.value_and_derivative
+ForwardDiff.value_and_derivatives
 ```
 
 ## Gradients of `f(x::AbstractArray)::Real`
diff --git a/src/derivative.jl b/src/derivative.jl
index b39e2a48..2042b836 100644
--- a/src/derivative.jl
+++ b/src/derivative.jl
@@ -75,6 +75,32 @@ end
 derivative(f, x::AbstractArray) = throw(DimensionMismatch("derivative(f, x) expects that x is a real number. Perhaps you meant gradient(f, x)?"))
 derivative(f, x::Complex) = throw(DimensionMismatch("derivative(f, x) expects that x is a real number (does not support Wirtinger derivatives). Separate real and imaginary parts of the input."))
 
+"""
+    ForwardDiff.value_and_derivative(f, x::Real)
+
+Return `f(x)` and `df/dx` evaluated at `x` in a single pass, assuming `f` is called as `f(x)`.
+
+This method assumes that `isa(f(x), Union{Real,AbstractArray})`.
+"""
+@inline function value_and_derivative(f::F, x::R) where {F,R<:Real}
+    T = typeof(Tag(f, R))
+    ydual = f(Dual{T}(x, one(x)))
+    return value(T, ydual), extract_derivative(T, ydual)
+end
+
+"""
+    ForwardDiff.value_and_derivatives(f, x::Real)
+
+Return `f(x)` and its first and second derivatives evaluated at `x` in a single pass, assuming `f` is called as `f(x)`.
+
+This method assumes that `isa(f(x), Union{Real,AbstractArray})`.
+"""
+@inline function value_and_derivatives(f::F, x::R) where {F,R<:Real}
+    T = typeof(Tag(f, typeof(x)))
+    ydual, ddual = value_and_derivative(f, Dual{T}(x, one(x)))
+    return value(T, ydual), value(T, ddual), extract_derivative(T, ddual)
+end
+
 #####################
 # result extraction #
 #####################
diff --git a/test/DerivativeTest.jl b/test/DerivativeTest.jl
index dfdd8ed2..d6697f3e 100644
--- a/test/DerivativeTest.jl
+++ b/test/DerivativeTest.jl
@@ -22,11 +22,22 @@ for f in DiffTests.NUMBER_TO_NUMBER_FUNCS
     v = f(x)
     d = ForwardDiff.derivative(f, x)
     @test isapprox(d, Calculus.derivative(f, x), atol=FINITEDIFF_ERROR)
+    d2 = ForwardDiff.derivative(x -> ForwardDiff.derivative(f, x), x)
 
     out = DiffResults.DiffResult(zero(v), zero(v))
     out = ForwardDiff.derivative!(out, f, x)
     @test isapprox(DiffResults.value(out), v)
     @test isapprox(DiffResults.derivative(out), d)
+
+    out = ForwardDiff.value_and_derivative(f, x)
+    @test length(out) == 2
+    @test isapprox(out[1], v)
+    @test isapprox(out[2], d)
+
+    out = ForwardDiff.value_and_derivatives(f, x)
+    @test isapprox(out[1], v)
+    @test isapprox(out[2], d)
+    @test isapprox(out[3], d2)
 end
 
 for f in DiffTests.NUMBER_TO_ARRAY_FUNCS