diff --git a/src/LegendSpecFits.jl b/src/LegendSpecFits.jl
index a40b44b6..e1f48498 100644
--- a/src/LegendSpecFits.jl
+++ b/src/LegendSpecFits.jl
@@ -86,6 +86,8 @@ include("calfunc.jl")
 include("sipm_simple_calibration.jl")
 include("sipmfit.jl")
 include("sipm_filter_optimization.jl")
+include("par_grid_binned_mc_result.jl")
+
 abstract type UncertTag end
 ForwardDiff.:(≺)(::Type{<:ForwardDiff.Tag}, ::Type{UncertTag}) = true
 ForwardDiff.:(≺)(::Type{UncertTag}, ::Type{<:ForwardDiff.Tag}) = false
diff --git a/src/par_grid_binned_mc_result.jl b/src/par_grid_binned_mc_result.jl
new file mode 100644
index 00000000..a9481dff
--- /dev/null
+++ b/src/par_grid_binned_mc_result.jl
@@ -0,0 +1,80 @@
+# This file is a part of LegendSpecFits.jl, licensed under the MIT License (MIT).
+
+using ArraysOfArrays
+
+"""
+    struct ParGridBinnedMCResult{M,N,parnames}
+
+Represents the result of a binned Monte Carlo simulation on a parameter grid.
+
+Example:
+
+```julia
+data = ParGridBinnedMCResult(
+    (a = 1:0.5:5, b = -3:1:3),
+    (0:0.1:100, 0:0.25:200),
+    ArrayOfSimilarArrays{Int,2,2}(rand(0:999, 1001, 801, 9, 7))
+)
+
+p = (a = 2.3, b = 0.7)
+interpolate_counts(data, p)
+````
+"""
+struct ParGridBinnedMCResult{
+	M,N,parnames,
+	PG<:NamedTuple{parnames,<:Tuple{Vararg{AbstractVector{<:Real},N}}},
+	BE<:Tuple{Vararg{AbstractVector{<:Real},M}},
+	Cts<:AbstractArray{<:AbstractArray{<:Real,M},N}
+}
+    par_grid::PG
+	bin_edges::BE
+	bin_counts::Cts
+end
+export ParGridBinnedMCResult
+
+
+# ToDo: Add ctor from Histograms.
+
+
+"""
+    LegendSpecFits.interpolate_counts(data::ParGridBinnedMCResult{parnames}))
+    LegendSpecFits.interpolate_counts(data::ParGridBinnedMCResult{parnames}, par_point::NamedTuple{parnames})
+
+Interpolate the binned counts in `data` at the given parameter point
+`par_point` via (multi-)linear interpolation.
+
+Curries when called with only `data`:
+
+```julia
+f = interpolate_counts(data)
+f(par_point) == interpolate_counts(data, par_point)
+```
+"""
+function interpolate_counts end
+
+interpolate_counts(data::ParGridBinnedMCResult{parnames}) = Base.Fix1(interpolate_counts, data)
+
+function interpolate_counts(data::ParGridBinnedMCResult{parnames}, par_point::NamedTuple{parnames}) where parnames
+    # ToDo: Handle out-of-bounds points (throw error, no extrapolation).
+
+	(;par_grid, bin_counts) = data
+	grid = values(par_grid)>
+	p = values(par_point)
+	idxs_lower = map(searchsortedlast, grid, p)
+	idxs_upper = map(searchsortedfirst, grid, p)
+	p_lower = map(getindex, grid, idxs_lower)
+	p_upper = map(getindex, grid, idxs_upper)
+	w_lower = map(_interpolation_weight_l, p, p_lower, p_upper)
+	w_upper = one(eltype(w_lower)) .- w_lower
+
+    # ToDo ...
+end
+
+function _interpolation_weight_l(x, l, h)
+	@assert l <= x <= h
+	tmp_w = (x - l) / (h - l)
+	R = typeof(tmp_w)
+	w = ifelse(l ≈ h, one(R), tmp_w)
+	@assert zero(R) <= w <= one(R)
+	return w
+end
diff --git a/test/runtests.jl b/test/runtests.jl
index 57db99ab..3cf8cfbc 100644
--- a/test/runtests.jl
+++ b/test/runtests.jl
@@ -14,5 +14,6 @@ Test.@testset "Package LegendSpecFits" begin
     include("test_lq.jl")
     include("test_aoe.jl")
     include("test_simplecal.jl")
+    include("test_par_grid_binned_mc_result.jl")
     isempty(Test.detect_ambiguities(LegendSpecFits))
 end # testset
diff --git a/test/test_par_grid_binned_mc_result.jl b/test/test_par_grid_binned_mc_result.jl
new file mode 100644
index 00000000..122a2046
--- /dev/null
+++ b/test/test_par_grid_binned_mc_result.jl
@@ -0,0 +1,23 @@
+# This file is a part of LegendSpecFits.jl, licensed under the MIT License (MIT).
+
+using LegendSpecFits
+using Test
+
+using ArraysOfArrays
+
+using LegendSpecFits: ParGridBinnedMCResult, interpolate_counts
+
+
+@testset "par_grid_binned_mc_result" begin
+    data = ParGridBinnedMCResult(
+        (a = 1:0.5:5, b = -3:1:3),
+        (0:0.1:100, 0:0.25:200),
+        ArrayOfSimilarArrays{Int,2,2}(rand(0:999, 1001, 801, 9, 7))
+    )
+
+    p = (a = 2.3, b = 0.7)
+    @test @inferred(interpolate_counts(data)) isa Function
+    @test @inferred(interpolate_counts(data, p)) == @inferred(interpolate_counts(data)(p))
+
+    # ToDo: Test correctness of interpolation!
+end